The document discusses MySQL NDB 8.0 and high availability solutions for MySQL. It summarizes MySQL NDB Cluster, MySQL InnoDB Cluster, and MySQL Replication as high availability solutions. It also discusses features and performance of MySQL NDB Cluster 8.0, including linear scalability, predictable low-latency performance, and improved backup throughput.
Connector/J Beyond JDBC: the X DevAPI for Java and MySQL as a Document StoreFilipe Silva
The document discusses Connector/J Beyond JDBC and the X DevAPI for Java and MySQL as a Document Store. It provides an agenda that includes an introduction to MySQL as a document store, an overview of the X DevAPI, and how the X DevAPI is implemented in Connector/J. The presentation aims to demonstrate the X DevAPI for developing CRUD-based applications and using MySQL as both a relational database and document store.
This document discusses two high availability solutions for MySQL: InnoDB Cluster and NDB Cluster. InnoDB Cluster provides high availability using MySQL 5.7+ features like Group Replication and allows for read scalability and application failover using MySQL Router. NDB Cluster uses an in-memory database with automatic sharding and native high availability features in the NDB storage engine. The document compares the two solutions and outlines some of their key differences like consistency models, sharding capabilities, and operational complexity.
MySQL 8.0 is the latest Generally Available version of MySQL. This session will give a brief introduction to MySQL 8.0 and help you upgrade from older versions, understand what utilities are available to make the process smoother and also understand what you need to bear in mind with the new version and considerations for possible behaviour changes and solutions. It really is a simple process.
MySQL can now be used as a document store, combining the flexibility of the document store model with the power of the relational model. You’ll understand why you’ll be able to choose MySQL for your Relational AND Document Store needs, avoiding significant trade-offs and being forced into choosing multiple solutions.
Upgrade to MySQL 5.7 and latest news planned for MySQL 8Ted Wennmark
The document discusses upgrading to MySQL 5.7 from previous versions. It provides an agenda that covers MySQL 5.7, upgrading to MySQL 5.7, and MySQL 8. It then discusses reasons to upgrade including performance/scalability improvements in MySQL 5.7, new features in 5.7 like JSON support and optimizer improvements, staying on a fully supported release, and security improvements in 5.7. Benchmarks show MySQL 5.7 is up to 6x faster than previous versions on OLTP workloads.
This document provides an overview of MySQL high availability solutions including InnoDB Cluster and NDB Cluster. InnoDB Cluster allows setting up a highly available MySQL cluster with auto-sharding using Group Replication and MySQL Router for transparent application routing. NDB Cluster is a memory-optimized database for low-latency applications requiring high scalability and availability. MySQL Shell provides a unified interface for deploying, managing and monitoring these MySQL HA solutions.
Mysql User Camp : 20th June - Mysql New FeaturesTarique Saleem
This document discusses new features in MySQL 5.7 and NoSQL support in MySQL. Some key points:
- MySQL 5.7 includes improvements to InnoDB for better transactional performance and scalability, as well as enhancements to replication, security, and other areas.
- NoSQL support allows direct access to MySQL data via Memcached APIs for simpler and faster key-value access while maintaining ACID guarantees.
- Benchmarks show NoSQL inserts into MySQL can be up to 9x faster than SQL inserts, and MySQL 5.7 can achieve over 1 million queries per second.
Connector/J Beyond JDBC: the X DevAPI for Java and MySQL as a Document StoreFilipe Silva
The document discusses Connector/J Beyond JDBC and the X DevAPI for Java and MySQL as a Document Store. It provides an agenda that includes an introduction to MySQL as a document store, an overview of the X DevAPI, and how the X DevAPI is implemented in Connector/J. The presentation aims to demonstrate the X DevAPI for developing CRUD-based applications and using MySQL as both a relational database and document store.
This document discusses two high availability solutions for MySQL: InnoDB Cluster and NDB Cluster. InnoDB Cluster provides high availability using MySQL 5.7+ features like Group Replication and allows for read scalability and application failover using MySQL Router. NDB Cluster uses an in-memory database with automatic sharding and native high availability features in the NDB storage engine. The document compares the two solutions and outlines some of their key differences like consistency models, sharding capabilities, and operational complexity.
MySQL 8.0 is the latest Generally Available version of MySQL. This session will give a brief introduction to MySQL 8.0 and help you upgrade from older versions, understand what utilities are available to make the process smoother and also understand what you need to bear in mind with the new version and considerations for possible behaviour changes and solutions. It really is a simple process.
MySQL can now be used as a document store, combining the flexibility of the document store model with the power of the relational model. You’ll understand why you’ll be able to choose MySQL for your Relational AND Document Store needs, avoiding significant trade-offs and being forced into choosing multiple solutions.
Upgrade to MySQL 5.7 and latest news planned for MySQL 8Ted Wennmark
The document discusses upgrading to MySQL 5.7 from previous versions. It provides an agenda that covers MySQL 5.7, upgrading to MySQL 5.7, and MySQL 8. It then discusses reasons to upgrade including performance/scalability improvements in MySQL 5.7, new features in 5.7 like JSON support and optimizer improvements, staying on a fully supported release, and security improvements in 5.7. Benchmarks show MySQL 5.7 is up to 6x faster than previous versions on OLTP workloads.
This document provides an overview of MySQL high availability solutions including InnoDB Cluster and NDB Cluster. InnoDB Cluster allows setting up a highly available MySQL cluster with auto-sharding using Group Replication and MySQL Router for transparent application routing. NDB Cluster is a memory-optimized database for low-latency applications requiring high scalability and availability. MySQL Shell provides a unified interface for deploying, managing and monitoring these MySQL HA solutions.
Mysql User Camp : 20th June - Mysql New FeaturesTarique Saleem
This document discusses new features in MySQL 5.7 and NoSQL support in MySQL. Some key points:
- MySQL 5.7 includes improvements to InnoDB for better transactional performance and scalability, as well as enhancements to replication, security, and other areas.
- NoSQL support allows direct access to MySQL data via Memcached APIs for simpler and faster key-value access while maintaining ACID guarantees.
- Benchmarks show NoSQL inserts into MySQL can be up to 9x faster than SQL inserts, and MySQL 5.7 can achieve over 1 million queries per second.
The document discusses Oracle's MySQL Cloud Service which provides MySQL as a database service on Oracle Public Cloud. Key features include automated backups, patching, monitoring, elastic scaling, high availability, security features from MySQL Enterprise Edition, and tools for data access, migration and restoration. The service runs MySQL 5.7 Enterprise Edition with an optimized configuration for the cloud environment.
This document provides an introduction to MySQL including its history and major milestones. It discusses MySQL's role in the LAMP stack and its popularity as the world's most widely used open source database. It also summarizes MySQL's various storage engines, architectures, and recent releases. The document concludes with a discussion of MySQL's future focus and available high availability solutions.
The document discusses new features in MySQL 5.7 including enhanced performance and scalability, next generation application support, and availability features. Key points include the MySQL 5.7 release candidate being available with 2x faster performance than 5.6, new JSON support, improved GIS capabilities using Boost.Geometry, multi-threaded replication for faster slaves, and new group replication for multi-master clusters.
Introduction to MySQL, and its features with an explanation of the various processes that should be followed in order to have an efficient MySQL implementation.
MySQL Day Paris 2016 - MySQL as a Document StoreOlivier DASINI
MySQL Day Paris 2016 - MySQL as a Document Store
✔ Built on Proven SQL/InnoDB/Replication
✔ Schema-less/Relational/Hybrid
✔ ACID/Transactions
✔ CRUD/JSON/Documents
✔ Modern Dev API
✔ Modern/Efficient Protocol
✔ SQL Queries/Analytics over JSON Documents
✔ Transparent and Easy HA/Scaling/Sharding
This is a presentation at Bengaluru TechDay -October2019 for Oracle Database Admin and Architects presented by Karthik P R ( CEO Mydbops ). He explains the possible High Availability options in MySQL ecosystem.
https://www.meetup.com/All-India-Oracle-Users-Group-Bangalore-Chapter/events/265252214/
MySQL Fabric is an extensible framework for managing high availability and sharding across a farm of MySQL servers. It allows creating high availability groups, adding MySQL servers to those groups to manage redundancy and load balancing. The framework includes connectors, a central node to manage the farm, and extensions for high availability and sharding functionality.
Python Utilities for Managing MySQL DatabasesMats Kindahl
Managing a MySQL database server can become a full time job. What we need are tools that bundle a set of related tasks into a common utility. While there are several such utility libraries to choose, it is often the case that you need to customize them to your needs. The MySQL Utilities library is the answer to that need. It is open source so you can modify and expand it as you see fit.
This is the presentation from OSCON 2011 in Portland.
Presented at Percona Live Amsterdam 2016, this is an in-depth look at MariaDB Server right up to MariaDB Server 10.1. Learn the differences. See what's already in MySQL. And so on.
NOSQL Meets Relational - The MySQL Ecosystem Gains More FlexibilityIvan Zoratti
Colin Charles gave a presentation comparing SQL and NoSQL databases. He discussed why organizations adopt NoSQL databases like MongoDB for large, unstructured datasets and rapid development. However, he argued that MySQL can also handle these workloads through features like dynamic columns, memcached integration, and JSON support. MySQL addresses limitations around high availability, scalability, and schema flexibility through tools and plugins that provide sharding, replication, load balancing, and online schema changes. In the end, MySQL with the right tools is capable of fulfilling both transactional and NoSQL-style workloads.
Webseminar: MariaDB Enterprise und MariaDB Enterprise ClusterMariaDB Corporation
This document provides information about MariaDB Enterprise and MariaDB Enterprise Cluster from Ralf Gebhardt, including:
- An agenda covering MariaDB, MariaDB Enterprise, MariaDB Enterprise Cluster, services, and more info.
- Background on MariaDB, the MariaDB Foundation, MariaDB.com, and SkySQL.
- A timeline of MariaDB releases from 5.1 to the current 10.0 and Galera Cluster 10.
- An overview of key features and optimizations in MariaDB 10 like multi-source replication and improved query optimization.
- Mention of Fusion-IO page compression providing a 30% performance increase with atomic writes.
Differences between MariaDB 10.3 & MySQL 8.0Colin Charles
MySQL and MariaDB are becoming more divergent. Learn what is different from a high level. It is also a good idea to ensure that you use the correct database for the correct job.
This talk will explain best practices for upgrade techniques in MySQL. In deep dive, we will go over how to upgrade successfully to MySQL 8.0. Explain MySQL 8.0 upgrade specific challenges. Go over gotchas and best practices. Review the latest version of MySQL 8.0 and bug reports.
The document discusses the MySQL Document Store, which allows storing and querying JSON documents in MySQL databases. It introduces the components of the MySQL Document Store, including the MySQL server, JSON data type, X Plugin, X Protocol, X DevAPI, MySQL Shell and connectors. The X DevAPI provides a modern CRUD interface for working with document collections and documents. Documents can be accessed and queried using both the NoSQL-style X DevAPI and traditional SQL.
The document discusses new features in MySQL 5.7 related to replication. It covers improvements to usability through online reconfiguration of global transaction IDs and replication filters. It also describes enhanced replication monitoring using performance schema tables and improved applier performance through locking-based parallelism. The agenda includes sections on replication features in 5.7, news from development, and future plans.
OpenStack Days East -- MySQL Options in OpenStackMatt Lord
In most production OpenStack installations, you want the backing metadata store to be highly available. For this, the de facto standard has become MySQL+Galera. In order to help you meet this basic use case even better, I will introduce you to the brand new native MySQL HA solution called MySQL Group Replication. This allows you to easily go from a single instance of MySQL to a MySQL service that's natively distributed and highly available, while eliminating the need for any third party library and implementations.
If you have an extremely large OpenStack installation in production, then you are likely to eventually run into write scaling issues and the metadata store itself can become a bottleneck. For this use case, MySQL NDB Cluster can allow you to linearly scale the metadata store as your needs grow. I will introduce you to the core features of MySQL NDB Cluster--which include in-memory OLTP, transparent sharding, and support for active/active multi-datacenter clusters--that will allow you to meet even the most demanding of use cases with ease.
MySQL is commonly used as the default database in OpenStack. It provides high availability through options like Galera and MySQL Group Replication. Galera is a third party active/active cluster that provides synchronous replication, while Group Replication is a native MySQL plugin that also enables active/active clusters with built-in conflict detection. MySQL NDB Cluster is an alternative that provides in-memory data storage with automatic sharding and strong consistency across shards. Both Galera/Group Replication and NDB Cluster can be used to implement highly available MySQL services in OpenStack environments.
The document discusses Oracle's MySQL Cloud Service which provides MySQL as a database service on Oracle Public Cloud. Key features include automated backups, patching, monitoring, elastic scaling, high availability, security features from MySQL Enterprise Edition, and tools for data access, migration and restoration. The service runs MySQL 5.7 Enterprise Edition with an optimized configuration for the cloud environment.
This document provides an introduction to MySQL including its history and major milestones. It discusses MySQL's role in the LAMP stack and its popularity as the world's most widely used open source database. It also summarizes MySQL's various storage engines, architectures, and recent releases. The document concludes with a discussion of MySQL's future focus and available high availability solutions.
The document discusses new features in MySQL 5.7 including enhanced performance and scalability, next generation application support, and availability features. Key points include the MySQL 5.7 release candidate being available with 2x faster performance than 5.6, new JSON support, improved GIS capabilities using Boost.Geometry, multi-threaded replication for faster slaves, and new group replication for multi-master clusters.
Introduction to MySQL, and its features with an explanation of the various processes that should be followed in order to have an efficient MySQL implementation.
MySQL Day Paris 2016 - MySQL as a Document StoreOlivier DASINI
MySQL Day Paris 2016 - MySQL as a Document Store
✔ Built on Proven SQL/InnoDB/Replication
✔ Schema-less/Relational/Hybrid
✔ ACID/Transactions
✔ CRUD/JSON/Documents
✔ Modern Dev API
✔ Modern/Efficient Protocol
✔ SQL Queries/Analytics over JSON Documents
✔ Transparent and Easy HA/Scaling/Sharding
This is a presentation at Bengaluru TechDay -October2019 for Oracle Database Admin and Architects presented by Karthik P R ( CEO Mydbops ). He explains the possible High Availability options in MySQL ecosystem.
https://www.meetup.com/All-India-Oracle-Users-Group-Bangalore-Chapter/events/265252214/
MySQL Fabric is an extensible framework for managing high availability and sharding across a farm of MySQL servers. It allows creating high availability groups, adding MySQL servers to those groups to manage redundancy and load balancing. The framework includes connectors, a central node to manage the farm, and extensions for high availability and sharding functionality.
Python Utilities for Managing MySQL DatabasesMats Kindahl
Managing a MySQL database server can become a full time job. What we need are tools that bundle a set of related tasks into a common utility. While there are several such utility libraries to choose, it is often the case that you need to customize them to your needs. The MySQL Utilities library is the answer to that need. It is open source so you can modify and expand it as you see fit.
This is the presentation from OSCON 2011 in Portland.
Presented at Percona Live Amsterdam 2016, this is an in-depth look at MariaDB Server right up to MariaDB Server 10.1. Learn the differences. See what's already in MySQL. And so on.
NOSQL Meets Relational - The MySQL Ecosystem Gains More FlexibilityIvan Zoratti
Colin Charles gave a presentation comparing SQL and NoSQL databases. He discussed why organizations adopt NoSQL databases like MongoDB for large, unstructured datasets and rapid development. However, he argued that MySQL can also handle these workloads through features like dynamic columns, memcached integration, and JSON support. MySQL addresses limitations around high availability, scalability, and schema flexibility through tools and plugins that provide sharding, replication, load balancing, and online schema changes. In the end, MySQL with the right tools is capable of fulfilling both transactional and NoSQL-style workloads.
Webseminar: MariaDB Enterprise und MariaDB Enterprise ClusterMariaDB Corporation
This document provides information about MariaDB Enterprise and MariaDB Enterprise Cluster from Ralf Gebhardt, including:
- An agenda covering MariaDB, MariaDB Enterprise, MariaDB Enterprise Cluster, services, and more info.
- Background on MariaDB, the MariaDB Foundation, MariaDB.com, and SkySQL.
- A timeline of MariaDB releases from 5.1 to the current 10.0 and Galera Cluster 10.
- An overview of key features and optimizations in MariaDB 10 like multi-source replication and improved query optimization.
- Mention of Fusion-IO page compression providing a 30% performance increase with atomic writes.
Differences between MariaDB 10.3 & MySQL 8.0Colin Charles
MySQL and MariaDB are becoming more divergent. Learn what is different from a high level. It is also a good idea to ensure that you use the correct database for the correct job.
This talk will explain best practices for upgrade techniques in MySQL. In deep dive, we will go over how to upgrade successfully to MySQL 8.0. Explain MySQL 8.0 upgrade specific challenges. Go over gotchas and best practices. Review the latest version of MySQL 8.0 and bug reports.
The document discusses the MySQL Document Store, which allows storing and querying JSON documents in MySQL databases. It introduces the components of the MySQL Document Store, including the MySQL server, JSON data type, X Plugin, X Protocol, X DevAPI, MySQL Shell and connectors. The X DevAPI provides a modern CRUD interface for working with document collections and documents. Documents can be accessed and queried using both the NoSQL-style X DevAPI and traditional SQL.
The document discusses new features in MySQL 5.7 related to replication. It covers improvements to usability through online reconfiguration of global transaction IDs and replication filters. It also describes enhanced replication monitoring using performance schema tables and improved applier performance through locking-based parallelism. The agenda includes sections on replication features in 5.7, news from development, and future plans.
OpenStack Days East -- MySQL Options in OpenStackMatt Lord
In most production OpenStack installations, you want the backing metadata store to be highly available. For this, the de facto standard has become MySQL+Galera. In order to help you meet this basic use case even better, I will introduce you to the brand new native MySQL HA solution called MySQL Group Replication. This allows you to easily go from a single instance of MySQL to a MySQL service that's natively distributed and highly available, while eliminating the need for any third party library and implementations.
If you have an extremely large OpenStack installation in production, then you are likely to eventually run into write scaling issues and the metadata store itself can become a bottleneck. For this use case, MySQL NDB Cluster can allow you to linearly scale the metadata store as your needs grow. I will introduce you to the core features of MySQL NDB Cluster--which include in-memory OLTP, transparent sharding, and support for active/active multi-datacenter clusters--that will allow you to meet even the most demanding of use cases with ease.
MySQL is commonly used as the default database in OpenStack. It provides high availability through options like Galera and MySQL Group Replication. Galera is a third party active/active cluster that provides synchronous replication, while Group Replication is a native MySQL plugin that also enables active/active clusters with built-in conflict detection. MySQL NDB Cluster is an alternative that provides in-memory data storage with automatic sharding and strong consistency across shards. Both Galera/Group Replication and NDB Cluster can be used to implement highly available MySQL services in OpenStack environments.
Keith Larson, the MySQL Community Manager, gave an introduction to MySQL. He outlined MySQL's history from being started in the 1980s to its acquisition by Oracle. Larson then covered key MySQL concepts like storage engines, replication, partitioning, and clustering to provide high availability. He emphasized that MySQL remains free and open source for the community to use.
This document summarizes James Kreuziger's presentation on optimizing MySQL for Cascade Server. The presentation covered choosing a MySQL version and configuration, testing tools, and the results of testing different MySQL configurations and key block sizes on storage space usage and load performance. It was aimed at Cascade administrators and provided an overview of topics like hardware requirements, the InnoDB buffer pool, and recommended resources for MySQL configuration and optimization.
MySQL Group Replication provides a high availability multi-master replication solution for MySQL. It allows multiple MySQL instances to act as equal masters that can accept writes and remain available even if some instances fail. Transactions are synchronously committed across all members of the replication group to ensure consistency. Group Replication handles failure detection and recovery transparently through its use of group communication systems and built-in conflict detection. It provides a highly available, scalable and fully distributed database solution compared to traditional MySQL replication and clustering options.
This document provides an overview of MySQL Cluster, a distributed, in-memory database that provides high availability, scale-out, and real-time performance. Key points include:
- MySQL Cluster can scale linearly to handle massive workloads through data sharding and replication across nodes. It offers 99.9999% availability.
- It is open source and can be used standalone or with MySQL. Data is partitioned and distributed automatically across nodes with no single point of failure.
- It is used by many large companies and systems that require high throughput, low latency access to large datasets, including for telecom, gaming, and financial applications.
This document provides an overview of the key capabilities and requirements of MySQL NDB Cluster 8.0. It discusses the following:
- High availability with less than 30 seconds of downtime per year and predictable low latency transactions.
- Transparent distribution and replication across nodes, along with write and read scalability.
- Support for SQL, LDAP, file systems and other interfaces through plug-ins. Mixed OLTP and OLAP capabilities for real-time analytics.
- Requirements to handle concurrent and sequential failures automatically with in-memory storage and asynchronous operations.
The document provides an introduction to MySQL. It discusses the history and founders of MySQL, an overview of MySQL products, and what MySQL is. MySQL is defined as a relational database management system that is open source, fast, reliable, and easy to use. It can be used as a standalone database or as part of web applications like LAMP stacks. The document also demonstrates MySQL Workbench and how to get involved with the MySQL community. It provides next steps for learning more about MySQL development and certification opportunities.
MySQL Cluster is a database that provides in-memory real-time performance, web scalability, and 99.999% availability. It uses memory optimized tables with durability and can handle high volumes of both reads and writes simultaneously in a distributed, auto-sharding fashion while maintaining ACID compliance. It offers high availability through a shared nothing architecture with no single point of failure and self-healing capabilities.
Modeling Data and Queries for Wide Column NoSQLScyllaDB
Discover how to model data for wide column databases such as ScyllaDB and Apache Cassandra. Contrast the differerence from traditional RDBMS data modeling, going from a normalized “schema first” design to a denormalized “query first” design. Plus how to use advanced features like secondary indexes and materialized views to use the same base table to get the answers you need.
This document discusses various approaches for scaling MySQL databases. It begins with an overview of using replication between a master and slave server to offload reads. Additional approaches covered include load balancing reads across multiple slaves, sharding data across multiple database instances, using MySQL Fabric or Galera Cluster for high availability, and deploying a MySQL Cluster for high performance and redundancy. The document cautions that scaling databases comes with costs and challenges, and emphasizes starting with normalized data and monitoring growth.
- MySQL Cluster is a distributed, shared-nothing database that provides high performance, scalability, availability, and linear scalability.
- It uses a shared-nothing architecture with synchronous data replication across nodes to ensure high availability and data redundancy.
- New features in MySQL Cluster 7.1 focus on reducing the cost of operations through simplified management and monitoring tools and faster restarts.
NoSQL, as many of you may already know, is basically a database used to manage huge sets of unstructured data, where in the data is not stored in tabular relations like relational databases. Most of the currently existing Relational Databases have failed in solving some of the complex modern problems like:
• Continuously changing nature of data - structured, semi-structured, unstructured and polymorphic data.
• Applications now serve millions of users in different geo-locations, in different timezones and have to be up and running all the time, with data integrity maintained
• Applications are becoming more distributed with many moving towards cloud computing.
NoSQL plays a vital role in an enterprise application which needs to access and analyze a massive set of data that is being made available on multiple virtual servers (remote based) in the cloud infrastructure and mainly when the data set is not structured. Hence, the NoSQL database is designed to overcome the Performance, Scalability, Data Modelling and Distribution limitations that are seen in the Relational Databases.
A Survey of Advanced Non-relational Database Systems: Approaches and Applicat...Qian Lin
This document summarizes a survey of advanced non-relational database systems, their approaches, applications, and comparison to relational database management systems (RDBMS). It outlines the problem of scaling to meet new web-scale demands, describes how non-relational databases provide a solution by sacrificing consistency for availability and partition tolerance. Examples of non-relational databases are provided, including their data models, APIs, optimizations, and benefits compared to RDBMS such as improved scalability and fault tolerance.
The document provides an overview of MySQL and its uses. It discusses how MySQL is used by many large websites and companies due to its open source nature, performance, and ability to handle high volumes of traffic. It highlights how MySQL is widely used for web applications and is integrated with common web development stacks. It also summarizes how Oracle supports and invests in MySQL through engineering resources and new product features.
Database as a Service on the Oracle Database Appliance PlatformMaris Elsins
Speaker: Marc Fielding, Co-speaker: Maris Elsins.
Oracle Database Appliance provides a robust, highly-available, cost-effective, and surprisingly scalable platform for database as a service environment. By leveraging Oracle Enterprise Manager's self-service features, databases can be provisioned on a self-service basis to a cluster of Oracle Database Appliance machines. Discover how multiple ODA devices can be managed together to provide both high availability and incremental, cost-effective scalability. Hear real-world lessons learned from successful database consolidation implementations.
This document discusses handling massive writes for online transaction processing (OLTP) systems. It begins with an introduction and overview of the topics to be covered, including terminology, differences between massive reads versus writes, and potential solutions using relational databases, NoSQL databases, and code optimizations. Specific solutions discussed for massive writes include using memory, fast disks, caching, column-oriented databases, SQL tuning, database partitioning, reading from slaves, and sharding or splitting data across multiple databases. The document provides pros and cons of each approach and examples of performance improvements observed.
Ted Wennmark provides an overview of MySQL 8.0 and the upgrade process from previous versions. Key points include performance and scalability improvements in MySQL 8.0, new features like common table expressions and roles, and a shift to a continuous delivery release model. It is recommended to upgrade directly from 5.7 to 8.0 by moving through each minor release, and to use MySQL Shell's upgrade checker tool to identify any potential issues.
MySQL Backup
Backup is one of the most critical tasks of database administration. In this webinar we will show you which options are available to run Backups of your MySQL databases and how different backup architectures support backups with minimal impact to ongoing operation of your application. Learn about online backups, quick restores, backup to cloud storage and encryption of backup data. All important features to run a professional, secure and performance backup environment.
This document discusses database security and best practices for securing MySQL databases. It covers common database vulnerabilities like poor configurations, weak authentication, lack of encryption, and improper credential management. It also discusses database attacks like SQL injection and brute force attacks. The document provides recommendations for database administrators to properly configure access controls, encryption, auditing, backups and monitoring to harden MySQL databases.
MySQL 5.6, news in 5.7 and our HA optionsTed Wennmark
Join us for this free MySQL Tech Tour to learn straight from the source how you can benefit from Oracle’s latest MySQL innovations. Our technical experts will help you understand how to take advantage of the wide range of new features and enhancements available in MySQL Fabric, MySQL 5.6, MySQL Cluster and other MySQL solutions. They will share tips & tricks to help you get the most of your database. You will also discover what’s coming next in MySQL 5.7.
MySQL Fabric - High Availability & Automated Sharding for MySQLTed Wennmark
The document discusses MySQL Fabric, which provides an extensible framework for high availability and sharding of MySQL databases. It allows clustering of MySQL servers for transparent failover and scale-out through sharding. MySQL Fabric handles shard mapping, global transactions and rebalancing shards across server groups. It provides connectors for applications to access the sharded and replicated database infrastructure with normal SQL queries.
This document discusses MySQL Enterprise Monitor, a tool for monitoring MySQL database performance. It can monitor MySQL databases, operating system resources, and query performance. The tool collects data without installing agents on the databases. It provides advisors, alerts and visualizations to help users identify and address issues. It aims to help database administrators ensure database availability, optimize performance, and plan for capacity needs.
Our (Olle from King and myself) session at OOW2014 (MySQL Central).
You will learn about the setup at King and also have a brief introduction to scaling MySQL.
My MySQL and NoSQL presentation from the NoSQL Search event in Copenhagen: http://nosqlroadshow.com/nosql-cph-2013/speaker/Ted+Wennmark
MySQL offers solutions to implement NoSQL concepts like auto-sharding, key-value access or asynchronous operations. This adds all known solutions from the SQL world to the NoSQL space.
The combined approach of SQL and NoSQL gives developers the choice to select whatever features from both worlds they need.
In this talk we take a deeper look at key-value access to MySQL and MySQL Cluster, auto-sharding and scalability of MySQL Cluster, mapping of schemaless key value access to a relational data model and the performance of NoSQL access to MySQL.
The document summarizes new features in MySQL 5.6 and MySQL Cluster 7.3. MySQL 5.6 includes improvements to InnoDB for better transactional performance and availability, improvements to the optimizer for better query execution and diagnostics, enhancements to replication for higher availability and data integrity, and new performance schema instrumentation. It also provides details on InnoDB enhancements for read-only workloads, online DDL operations, full text search on InnoDB tables, and improved scalability seen in sysbench benchmarks. MySQL Cluster 7.3 is also mentioned but no details are given.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
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This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Open Source Contributions to Postgres: The Basics POSETTE 2024ElizabethGarrettChri
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Kaxil Naik
Navigating today's data landscape isn't just about managing workflows; it's about strategically propelling your business forward. Apache Airflow has stood out as the benchmark in this arena, driving data orchestration forward since its early days. As we dive into the complexities of our current data-rich environment, where the sheer volume of information and its timely, accurate processing are crucial for AI and ML applications, the role of Airflow has never been more critical.
In my journey as the Senior Engineering Director and a pivotal member of Apache Airflow's Project Management Committee (PMC), I've witnessed Airflow transform data handling, making agility and insight the norm in an ever-evolving digital space. At Astronomer, our collaboration with leading AI & ML teams worldwide has not only tested but also proven Airflow's mettle in delivering data reliably and efficiently—data that now powers not just insights but core business functions.
This session is a deep dive into the essence of Airflow's success. We'll trace its evolution from a budding project to the backbone of data orchestration it is today, constantly adapting to meet the next wave of data challenges, including those brought on by Generative AI. It's this forward-thinking adaptability that keeps Airflow at the forefront of innovation, ready for whatever comes next.
The ever-growing demands of AI and ML applications have ushered in an era where sophisticated data management isn't a luxury—it's a necessity. Airflow's innate flexibility and scalability are what makes it indispensable in managing the intricate workflows of today, especially those involving Large Language Models (LLMs).
This talk isn't just a rundown of Airflow's features; it's about harnessing these capabilities to turn your data workflows into a strategic asset. Together, we'll explore how Airflow remains at the cutting edge of data orchestration, ensuring your organization is not just keeping pace but setting the pace in a data-driven future.
Session in https://budapestdata.hu/2024/04/kaxil-naik-astronomer-io/ | https://dataml24.sessionize.com/session/667627
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
1. Ted Wennmark & Stuart Davey
MySQL Solution Engineering EMEA
MySQL Business Unit
February 24, 2021
MySQL News
MySQL NDB 8.0
2. Safe harbor statement
The following is intended to outline our general product direction. It is intended for information
purposes only, and may not be incorporated into any contract. It is not a commitment to deliver
any material, code, or functionality, and should not be relied upon in making purchasing
decisions.
The development, release, timing, and pricing of any features or functionality described for
Oracle’s products may change and remains at the sole discretion of Oracle Corporation.
2
3. • Long time MySQL user
– Started developing apps using MySQL over 20 years back
– Worked as MySQL DBA, Trainer and consultant the past
• MySQL Prinicipal Solution Architect at Oracle
• Work with normal MySQL but have focuse on distributed
databases with NDB Cluster.
• My workshops at Github: https://github.com/wwwted/
• Let’s stay in touch:
– https://www.linkedin.com/in/tedwennmark/
• Join us on slack: https://lefred.be/mysql-community-on-slack/
Ted Wennmark
3
4. MySQL High Availability Solutions
• MySQL NDB Cluster
– NDB storage engine.
– Memory database.
– Automatic sharding of data.
– SQL Access via MySQL with
cross shard join support.
– Native access via several
API’s.
– Read/write consistency.
– Read/write scalability (2pc).
– ACID and transactions.
• MySQL InnoDB Cluster
– Easy HA built into MySQL
5.7+ for InnoDB.
– MySQL Group Replication,
Shell and Router.
– Write consistency.
– Read Scalability.
– Native CRUD API in
MySQL 8.
– Synchrounous (Paxos).
• MySQL Replication
– Core part of MySQL, used
by almost everyone.
– Can be used by any
storage engine.
– Asynchronous and semi-
sync option.
– Scale out reads.
– ReplicaSet from 8.0.19 with
integration to Shell and
Router.
4
5. MySQL High Availability Solutions
• MySQL NDB Cluster
– NDB storage engine.
– Memory database.
– Automatic sharding of data.
– SQL Access via MySQL with
cross shard join support.
– Native access via several
API’s.
– Read/write consistency.
– Read/write scalability (2pc).
– ACID and transactions.
• MySQL InnoDB Cluster
– Easy HA built into MySQL
5.7+ for InnoDB.
– MySQL Group Replication,
Shell and Router.
– Write consistency.
– Read Scalability.
– Native CRUD API in
MySQL 8.
– Synchrounous (Paxos).
• MySQL Replication
– Core part of MySQL, used
by almost everyone.
– Can be used by any
storage engine.
– Asynchronous and semi-
sync option.
– Scale out reads.
– ReplicaSet from 8.0.19 with
integration to Shell and
Router.
5
6. Massively linear scale
Always-On 99.9999% Availability
Distributed In-Memory Datasets
Always Consistent
Parallel Real-Time Performance.
Auto-partitioning, data distribution
and replication built-in.
Read- and Write Scale-Out
to many TB on commodity hardware.
Designed for mission critical
systems. Masterless, shared-nothing
with no single point of failure.
Transactional consistency across
distributed and partitioned dataset.
Out of the box straightforward
application programming.
Ease of use
Open Source
Written in C++. Can be used standalone
or with MySQL as a SQL front-end.
6
7. Requirements on NDB Cluster
• Unavailable less than 30 seconds per year (Class 6)
• Predictable latency (transaction with 20 operations within 10 milliseconds, mixed
read/write)
• Transparent Distribution and Replication
• Write and Read Scalability
• Support SQL, LDAP, File System interface, …
• Mixed OLTP and OLAP for real-time data analysis
• Follow HW development on CPUs, Network, Disks and Memory
7
8. Class 6 Availability
• Handle many concurrent and sequential failures
• Automatic restart at failure
• Synchronize with live nodes
• Online schema changes
• Global Replication
• Online Add Node
8
9. Predictable Latency - Real-time
• Defaults to In-Memory storage
• Asynchronous File Operations
• Complex operations divided into multiple executions
• Memory lockable to avoid swapping
• Real-time mode supported
• CPU spinning modes supported
9
10. When TO consider MySQL Cluster
• You need High Availability 6-9’s (and strong consistency).
• You need Sharding, either due to size or write
performance.
• You need Linear Scalabillity when adding more nodes.
• You need predictable Real-ime response times.
• SQL and cross shard join support.
• You want a ACID distributed in-memory database.
10
12. MySQL Cluster NoSQL Performance
200 Million NoSQL Reads/Second
• Memory optimized tables
− Durable
− Mix with disk-based tables
• Parallel table scans for non-indexed
searches
• MySQL Cluster FlexAsych
− 200M NoSQL Reads/Second
12
13. MySQL Cluster SQL Performance
2.5M SQL Statements/Second
• Memory optimized tables
− Durable
− Mix with disk-based tables
• Massively concurrent OLTP
• Distributed Joins for analytics
• Parallel table scans for non-indexed
searches
• MySQL Cluster DBT2 BM
− 2.5M SQL Statements/Second
13
14. YCSB Benchmark
YCSB : Yahoo Cloud Serving Benchmark
• YCSB – Yahoo Cloud Service Benchmark
− De-facto cloud benchmark
− Benchmark can not be changed
• NDB is #1 player in this realm
− NDB Cluster is the Fastest Distributed, In-memory, Transactional Database in
the world!
14
15. YCSB Benchmark – Scaling NBD
YCSB : Yahoo Cloud Serving Benchmark
YCSB 0.15.0 with JDBC / SQL
• 1kB records
• Uniform distribution
2, 4 and 8 data nodes
• Replication factor 2
• ACID (read committed)
8 DenseIO across 2 AD
• adding 400us network latency
Best throughput and latency on market
1M
2M
3M
4M
2 4 8
(2 ADs)
1.4M
2.8M
3.7M
Transactions
per
second
Nodes
15
16. YCSB Benchmark – NDB Real-Time
YCSB : Yahoo Cloud Serving Benchmark
4 data nodes with 300M and
600M rows using JDBC
99% SQL reads < 1ms
• 95% < 0.9ms
99% SQL writes < 2ms
• 95% < 1.7ms
1M
Transaction
per
second
2 ms
Same Throughput & Latency
300M rows 600M rows
1.25M
TPS
1.25M
TPS
Reads
Reads
Writes
Writes
1 ms
16
17. Product Nodes TPS/OPS
32 227k
2 275k
3 715k
6 1.6M
8 1.6M
4 2.8M
YCSB Benchmark – NDB Results
YCSB : Yahoo Cloud Serving Benchmark
• Developed at Yahoo for Cloud Scale
workloads
• Widely used to compare scale-out
databases, NoSQL databases, and (non-
durable) in-memory data grids
• A series of NoSQL workload types are
defined:
• Workload A: 50% reads, 50% Updates
• The YCSB Client cannot be changed
• DB Vendors implement the DB Client
interface in Java
17
19. MySQL Cluster Architecture
• Multiple data nodes form a cluster
• Shared nothing architecture
• Data is automatically distributed to data
nodes
19
20. MySQL Cluster Architecture - Replicas
Copy of 1
Copy of 1
• Multiple copies of data are maintained for
availability
• A group of data nodes shares the same
data
• 1 - 4 replicas/copies of data can be
configured
20
21. User-id (PK) Service Data
1773467253 chat xxx
6257346892 chat xxx
1773467253 photos xxx
7234782739 photos xxx
8235602099 reminders xxx
8437829249 location xxx
MySQL Cluster Data Nodes
Partition Key
Data distribution
• Auto-partitioning and distribution
− No name-node or central master
• Each dataset is split into fragments and
distributed across data nodes.
• Within a cluster data is always consistent.
21
27. On-line Scaling and Elasticity - Repartitioning
Virtual partitions re-distributed on-line when adding more data nodes
Designed to be a slow background process not impacting real-time performance.
27
28. On-line Scaling and Elasticity - Repartitioning
Minimal amount of data moved
No re-hashing necessary
Similar to consistent hashing
28
29. Fully replicated
• Datasets can be marked to be copied to all nodes for best possible read performance
• All copies can be configured to be read from
• Local copy can be preferred when reading
29
30. Writing data “ACID”
Data
Memory
Flush writes to disk in
background checkpoints
Commit Log (REDO)
writes
…
time
…
• Data in MySQL Cluster is written to
memory and disk in a way that allows
real-time access and recovery
• Memory is locked so it won’t swap
• Writes go to data memory and commit
log
• Background process checkpoints data
memory for recovery
• Reads always happen from memory - not
from disk
30
31. Reading Data
• Cluster always knows where its data is - without a
name node
• Key-value with hash on primary key
• Complemented by ordered in-memory-optimized T-
Tree indexes for fast searches
31
32. Cross partition joins
• Cluster queries distributed data as
if it was a single consolidated
database
• Joins are pushed down to data
nodes
• Parallel cross-shard execution in
the data nodes
• Result consolidation in MySQL
Server
32
34. MySQL Cluster Development: 7.5 -> 8.0 (GA)
- MySQL Server 5.7 (5.6)
- 5x faster restarts
- JSON Support
- 50% faster reads
- 40% faster read/write
Cluster 7.4/7.5
Cluster 7.6
- MySQL Server 5.7
- Designed for Terabyte clusters
- Designed for modern hardware
- Native csv import
- Parallel backup
- Faster restart and recovery
Cluster 8.0 (GA)
- MySQL 8.0
- More Data nodes (144)
- 1-4 replicas
- Dynamic memory mgmt
- Larger rows (32k)
- Faster SQL
- Faster Disk Data
34
35. Cluster 8.0 Multi-threaded backup
Each data node doing own backup - one data
manager handling all writing
Now each data manager handling own
writing
Data Node 1 Data Node 2 Data Node 1 Data Node 2
35
36. Cluster 8.0 Multi-threaded backup
Now using all Local Data-Managers (LDM):
− Better system balance, avoids local data-manager overload
− Local Data-Manager with local backup processing - more efficient
− Faster backups (but backup performance limited more by configurable checkpoint speed,
so this is not necessarily true)
N independent file sets, can restore in parallel
36
37. Cluster 8.0 Transactional Data Dictionary
• Goal: Atomic and Transactional DDL for MySQL Server.
• Centralized data dictionary schema that uniformly stores dictionary data.
• Serialized dictionary format (SDI).
• MySQL Server local dictionary information is synchronized via NDB in a synchronous
fashion.
37
38. Cluster 8.0 Synchronized privileges I
• Privilege information moved from MyISAM to transactional InnoDB (but not part of Data
Dictionary).
• Changes in code due to data dictionary mandated removal of previous distributed privileges
implementation.
• Privileges are now synchronized via NDB and schema distribution.
38
39. Cluster 8.0 Synchronized privileges II
mysql>
GRANT
NDB_STORED_USER
ON
db.t1
TO
`bo-l-2`@`localhost`
NDBAPI
Local privilege
tables (InnoDB)
ACL
ndb_sql_metadata table
ACL Replication
Events
39
40. Cluster 8.0 Dynamic resource allocation
config.ini today
config.ini
MaxNoOfConcurrentTransactions=70000
MaxNoOfConcurrentOperations=359500
# Don't touch the following parameter
unless you really know what you're
doing.
MaxNoOfConcurrentScans=200
MaxNoOfLocalScans=9000
40
41. Cluster 8.0 Dynamic resource allocation
• Transactional memory dynamically
allocated from pool
• No more MaxNoOfTransactions,
MaxNoOfOperations, MaxNoOf…
• Still possible to use old static allocation
for highest level of performance
• More resources types to follow
config.ini
MaxNoOfConcurrentTransactions=90000
MaxNoOfConcurrentOperations=259200
# Don't touch the following parameter
unless you really know what you're
doing.
MaxNoOfConcurrentScans=300
MaxNoOfLocalScans=10000
41
42. Cluster 8.0 Dynamic resource allocation
• Transaction resources have a
reserved minimum and can
allocate up to a maximum
amount.
• Transaction resources will first
allocate from fixed size
Transaction Memory pool.
• If Transaction Memory pool is
exhausted then allocation will
happen from Shared Global
Memory - up to maximum per
resource.
Shared Global
Memory
Reserved
per resource
Global
maximum
Transaction
Memory
Concurrent
Operations
Concurrent
Transactions
Concurrent
Scans
Exclusive for
all transaction
resources
42
43. Cluster 8.0 Dynamic resource allocation
High-level gains:
− Less configuration complexity
− Fewer operational issues due to 'resource X exhausted’
− Potential savings on memory due to over-configured resources.
− Avoids hand-crafted config.ini for every new setup variant
43
44. Node 2
Node 1
Cluster 8.0 Reading from backup fragment is default
• Entirely local read transactions for co-
located API-nodes! Improved latency.
• Reading from backup allows to read any
node containing a copy of data
• Previously reads were directed towards
the node containing the primary fragment
only
44
45. Cluster 8 TPC-H Cluster 8.0 versus 7.5
Across all SQL NDB 8.0 is equally fast or faster than 7.5
NDB
8.0
x
times
faster
0,00
17,50
35,00
52,50
70,00
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 *) Q9 Q10 *) Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 *) Q19 Q20 Q21 Q22
Improvements made in 7.6 vs 7.5 Improvements made in 8.0 vs 7.6
45
46. Cluster 8.0 More New features
• Larger row sizes (14k -> 30k)
• Support for 4 replicas (max 2 today)
• Larger cluster:
− Up to 144 data nodes
46
50. MySQL Cluster Use Cases
• Key-Value store
+ High Availability, Scale-Out, Durability
• Transactional object store
+ Multi row transactions and consistency
• Relational database with MySQL Server front-ends
+ SQL joins, foreign keys, triggers, stored procedures, generated columns, JSON
50
51. SQL, JDBC, ADO, ...
LB or Connector/J
arbitrator
MySQL Cluster: SQL - Read Optimized HA setup
• Optimized 2 server HA setup, 3rd node
with management node is needed for
arbitration only.
• With ReadBackup all data is read/joined
locally.
• MySQL API nodes use shared memory
transporter (UseShm).
• MySQL nodes know who is local data
node using configuration parameter
ndb_data_node_neighbor.
51
52. application
Data Nodes
NDB Native C++ API
MySQL Cluster: Key-Value store
• High volume OLTP system.
• Linear scalability.
• Real-time response times.
• +50TB systems
• Use cases:
✓ IoT
✓ Financial data
✓ Telco core network data
52
53. Application(s)
NDB Native C++ API
App
SQL
MySQL Cluster: Hybrid “New SQL”
• High volume OLTP system.
• Linear scalability.
• Real-time response times.
• +50TB systems
• Access via SQL:
✓ Analytics
✓ BI
✓ Fraud
Data Nodes
53
54. Application(s)
Load Balancers
• High volume OLTP system.
• +50TB systems
• All access via SQL!
• Use cases:
✓ IoT
✓ On-line gaming
✓ Trading or other financial data
✓ Scalable SQL database
MySQL Cluster: New SQL
Data Nodes
54
55. Node Group 2
Node Group 1
Application(s)
Data Nodes
MySQL Cluster: DR – One Stretched Cluster I
Load Balancers
Application(s)
Load Balancers
DC 1 DC 2
55
56. MySQL Cluster: DR – One Stretched Cluster II
• This architecture will impact your response times if the latency is high
between the two data center.
− With the use of multithreaded applications and batching NDB can still deliver
good throughput.
− Timeouts for heartbeat can be increased if needed.
• Make sure you configure cluster so node groups are spanning both DC
as seen in picture above.
• This architecture is best used if you have a predictable low latency
network.
• Supports running application active on both sites (DC’s)
56
58. MySQL Cluster: DR – Asynchronous Replication II
• This architecture is our standard (Active/Passive) DR solution.
• Two independent NDB Custer on each site, no impact on response
times due to latency between the two sites (DS’s) since replication is
asynchronous.
• Asynchronous replication is not native to NDB so dedicated MySQL
nodes are need to take care of replication cross sites.
• Manual work is needed to manage the replication channel.
• Supports running application active/passive setup between sites (DC’s)
− Active/Active can be achieved using replication in both directions
and conflict resolution.
58
60. MySQL Replication vs InnoDB Cluster vs NDB Cluster
MySQL Replication MySQL InnoDB Cluster MySQL NDB Cluster
Storage Engine All InnoDB NDBCLUSTER
Distributed Architecture Shared Shared nothing Shared nothing
Clustering Mode Master + slaves Multi-master (possible) Multi-master (default)
Replication mode Asynchronous Paxos (Synchronous) 2PC (Synchronous)
Consistency Model Weak Consistency Medium Consistency Strong Consistency
Sharding No No Yes
Arbitration No Yes Yes
Load Balancing No Reads via MySQL Router Yes
NoSQL APIs MySQL CRUD API MySQL CRUD API Native NDB API
Operational Complexity Easy Medium High
Administration Standard (MySQL) Standard (MySQL) Custom (MySQL + NDB)
60