TDC2016SP - Trilha NoSQL
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Introdução e Detalhes Técnicos do Oracle NoSQL Database
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TDC2016SP - Trilha NoSQL
- 1. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Oracle NoSQL Database Overview & Use Cases Oracle Open World LAD 2016 Gustavo Castilhos Big Data Solutions Specialist Jun/2016
- 2. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Agenda Overview & Use Cases Oracle’s Big Data & NoSQL Strategy Technical Features Customer References 2
- 3. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Agenda Overview & Use Cases Oracle’s Big Data & NoSQL Strategy Technical Features Customer References 3
- 4. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | • Real time event processing • Sensor data acquisition/IoT • Fraud detection and prevention • Real time recommendations • Globally distributed databases • Social networks and online gaming Main reasons for enterprises adopting NoSQL: • Low cost • Performance • Scalability • Flexibility Why use a NoSQL database? 4 Fonte: Oracle, 2013
- 5. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | • Real time event processing • Sensor data acquisition/IoT • Fraud detection and prevention • Real time recommendations • Globally distributed databases • Social networks and online gaming Why use a NoSQL database? 5
- 6. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | • What an enterprise-class database should have: – Security – Durability – Transactions support – Hardware certifications – Integration between technologies – Means of administration – Reliable support • Common characteristics of NoSQL databases: – Few security features – Performance X Durability – No hardware certification – No “out-of-box” integration tools – Complex API’s – Support by niche companies The Challenges 6
- 7. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | 7 An Enterprise-Class NoSQL Database Oracle NoSQL Text Core Database Functionality Application Developer Friendly Software Manageability • Predictable, low latency • Highly available • Highly scalable • Administrator friendly (IT) • Strong Integration • Enterprise-grade support • Multiple high level API’s • Simple, flexible schemas
- 8. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Agenda Overview & Use Cases Oracle’s Big Data & NoSQL Strategy Technical Features Customer References 8
- 9. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Choose the RIGHT storage option for the job Hadoop Distributed File System (HDFS) Oracle NoSQL Database Oracle Database File System Key-Value Database Relational Database No inherent structure Simple data structure Complex data structures, rich SQL High volume writes High volume random reads and writes High volume OLTP with 2-PC Limited functionality, roll-your-own applications Simple get/put high speed storage, flex configuration Security, Backup/Restore, Data life cycle mgmt, XML, etc. Batch Oriented Real-Time, web-scale specialized applications General purpose SQL platform, multiple applications, ODBC, JDBC 9
- 10. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Oracle’s Big Data & NoSQL Strategy 10 Reference Architecture Actionable Events Data Lake Data Factory Data Warehouse BI and Reporting Discovery Lab Actionable Information Actionable Insights Data Streams Execution Innovation Discovery Output Events & Data Enterprise Data Web & Social Data Event Engine Model First Analytics • Reporting-oriented • Often enterprise wide in scope, cross LoB • “you know the questions to ask” Reports & Dashboards Data First Analytics • Data Exploration • Highly visual and/or interactive • “you don’t know the questions to ask” Discovery • Telematics • Industry Services • Internet of Things • Sentiment Data Services
- 11. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Oracle’s Big Data & NoSQL Strategy 11 Reference Architecture Actionable Events Data Lake Data Factory Data Warehouse BI and Reporting Discovery Lab Actionable Information Actionable Insights Data Streams Execution Innovation Discovery Output Events & Data Enterprise Data Web & Social Data Event Engine Model First Analytics • Reporting-oriented • Often enterprise wide in scope, cross LoB • “you know the questions to ask” Reports & Dashboards Data First Analytics • Data Exploration • Highly visual and/or interactive • “you don’t know the questions to ask” Discovery • Telematics • Industry Services • Internet of Things • Sentiment Data Services
- 12. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | RDBMS 12 Integrating the best of breed Oracle Big Data SQL One fast SQL query, on all your data, in parallel SQL
- 13. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Agenda Overview & Use Cases Oracle’s Big Data & NoSQL Strategy Technical Features Customer References 13
- 14. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Logical Architecture Linear scaling and replication 14 • Elastic Auto Sharding (split, add, contract) Store • Writes to elected node with flexible durability • Reads from any node in shard Expand and Rebalance Shard M R R Shard M Shard R R R R Application NoSQL Driver M Shard R R M • Auto re-balance of data on expansion
- 15. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Data Center Support • Availability Zones • Flexible configuration • Primary Zones – Durability guarantees – Low latency writes, HA • Secondary Read-Only Zones – Asynchronous replication – Analytic workloads – Report generation • Topology Aware Client Driver • Provides business continuity and distributed workload management 15 DC1 DC2 DC3 PrimaryZones Reports Batch Analytics
- 16. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Smart Topology Management • Efficient disk usage • No I/O bottlenecks • Smart cache sharing • Automatic switchover • Bigger cluster, lower TCO 16 Shard M Shard R R R R Application NoSQL Driver M Shard R R M Server #2 Server #1 Server #3
- 17. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Configurable Consistency vs Availability • Greater Flexibility – Configurable • Durability per operation • Consistency per operation – ACID by default – Transactions may be composed of multiple read/write operations 17
- 18. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | 18 Complex data. Simple management. Flexible Data Model advanced key-value database Compound Primary key & Shard key Automatic data sharding & local indexing Range queries on any indexed field 1. JSON structures, Tables, Arrays, Maps 2. BLOB’s, Multimedia 3. Graph structures
- 19. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Oracle NoSQL Database Cloud Service 23 Driver Application
- 20. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Agenda Overview & Use Cases Oracle’s Big Data & NoSQL Strategy Technical Features Customer References 24
- 21. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | NoSQL for Flight Test Analysis • Objectives: – Have a scalable and highly available storage for flight test sensor data – Allow simultaneous data ingestion and analysis • Solution: – Oracle NoSQL database • High speed storage and range based extraction of time series data • Agile, flexible schema, easily integrated with the existing application – Oracle Big Data Appliance: efficient manageability and lowest TCO – Integration with Hadoop and RDBMS for post processing 27 Large scale sensor data acquisition and processing Airbus
- 22. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | NoSQL for Flight Test Analysis • Benefits – Increase scalability of data storage – Deliver higher concurrency between data analytics and ingestion – Scale-out data loading independently from analysis – Enterprise-grade support for mission critical system – 750K key inserts/sec, 6TB/hour 28 Large scale sensor data acquisition and processing Big Data Appliance NoSQL DB Driver Event Ingestion and Extraction Oracle and/or third parties SQL/Data Analytics Tools Airbus
- 23. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Confidential 29
- 24. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Confidential 30
- 25. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Safe Harbor Statement The preceding 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, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle. 31
- 26. Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | 32
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- If we look at the various storage options available to handle Big Data – there are essentially three types: Hadoop, NoSQL Databases, Relational Databases HDFS is a great distributed file system. Parallel, highly scalable and no inherent structure. However, it’s tuned primarily for bulk sequential read/write of file blocks. There are no indices for fast access to specific data records, it’s not well suited for lots of small files or updating files that have already been written. Primarily a batch system, write lots of data, then read it all in parallel over and over. Sounds like a datawarehouse, but more unstructured. The Relational Database on the other hand, is usually deployed on a big machine, and supports complex data structures stored in tables with plenty of relationships. Data is manipulated and accessed using rich SQL to build mission critical applications. There is support for variety of data access protocols like ODBC/JDBC along with an elaborate life cycle management infrastructure involving security and backup/restore operations. Enterprises run their mission critical transaction processing systems on relational databases. NoSQL database is the middle ground: a distributed key-value database with a simple data structure. It has indices. It can handle large volumes of data and is usually deployed on a distributed architecture consisting of several small machines. It’s designed for low latency high volume reads and writes of simple data, that is typical with real-time and web-scale specialized applications. It’s not tuned for reading/writing huge files – use a file system for that. It has flex configuration capabilities that make it very suitable to rapid application development requirements. Data scalability at low cost.
- To summarize, Oracle Big Data SQL is…
- (mencionar no final do slide as api’s bulkPut, bulkGet, Graph + PatternMatching, BLOB’s + multimedia
- Hive Storage Handler was a 3.2 feature. Complex type support was A 3.4 feature.
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