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Welcome – Housekeeping Items
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Agenda
• Who is EDB
• Practices to help drive PostgreSQL adoption
• Understand the application landscape and the fit for
PostgreSQL
• Understand how to eat the elephant - one byte at a time
• Foster collaboration to drive adoption
• Use standardization to enable automation
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Genealogy of
Relational
Database
Management
Systems
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EDB team includes:
More PostgreSQL experts
• 300+ PostgreSQL technologists
• 26 PostgreSQL community contributors and committers
• Including founders and leaders like
Michael Stonebraker
“Father of Postgres”
and EDB Advisor
Bruce Momjian
Co-founder, PostgreSQL
Development Corporation
and EDB Employee
Peter Eisentraut
PostgreSQL leader
and EDB Employee
Robert Haas
PostgreSQL Major
Contributor, Committer
and EDB Employee
Simon Riggs
Enterprise PostgreSQL
Expert and EDB Employee
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EDB Postgres Advanced Server Feature
Highlights
EDB Feature Contributions
to PostgreSQL Core
PostgreSQL
Feature Highlights
v12
• Compound Triggers (OC)
• Interval Partitioning (OC)
• Aggregate Functions: Median & ListAgg (OC)
• CAST(Multiset) (OC)
• Six Additional Schema Views (OC)
• Pluggable Table Storage Capability
• WIP: Zheap Storage Engine Providing Better Control Over Bloat
• ATTACH PARTITION
• SERIALIZABLE for Parallel Query
• SQL/JSON Path Expression Support
• Optimized Common Table Expressions (CTE)
• Improved B-Tree Indexing
• Stored Generated Columns
• Security Improvements (LDAP and GSSAPI)
v11
• Data Redaction (OC)
• Autonomous transactions (OC)
• Performance Analytics
• Procedure Overloading
• Just-in-time (JIT) compilation using LLVM
• Multiple Parallelism Improvements (e.g.Hash Joins)
• Automatic Cache Pre-warm at Start-up
• Partitioned Table Improvements
• Performance Improvements for Very Large DBs
• SQL Stored Procedures with BEGIN, COMMIT / ROLLBACK
• Window Functions Support for SQL:2011 Standard
v10
• Re-direct Audit Log Records to syslog
• EDB Clone Schema
• Automatic Cache Pre-warm at Start-up
• Customizable WAL Segment Size
• Parallel Query (index, bitmap scans & merge joins)
• Durable Hash Indexes
• Postgres Foreign Data Wrapper Push Down of Joins and
Aggregates
• Trigger Transition Tables
• Logical Replication
• Declarative Table Partitioning
• Quorum Commit for Synchronous Replication
• SCRAM-SHA-256 authentication
v9.6
• Advanced Queuing (DBMS_AQ) (OC)
• Nested Sub-Procedures (OC)
• Partitioned Table Improvements
• EDBLoader Enhancements (OC)
• Parallel Hint Support (OC)
• Parallel Sequential Scans, Joins, and Aggregates
• Synchronous Replication Support for 2+ Standbys
• Multiple Performance Improvements
• Avoid Repetitive Autovacuum
• Full-text Search for Phrases
• Remote Joins, Sorts, Updates in postgres_fdw
• Cube Extension kNN support
• Index-only scans for partial indexes
OC = Oracle Compatible and usable for non-Oracle applications
Proven Leadership...Strongest Contributions to PostgreSQL
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EDB: Driving
Postgres forward
for 17 years
2019
Challengers Leaders
Niche Players Visionaries
Ability
to
execute
Completeness of
vision
1986
The design
of PostgreSQL
1996
Birth of
PostgreSQL
2004
EDB
is founded
2020
EDB acquires
2nd Quadrant
Materialized
Views
Parallel
Query
JIT
Compilation
Heap Only
Tuples (HOT)
Serializable
Parallel Query
2007
2ndQuadrant
launched
Logical
Replication
Transaction
Control
Hot
Standby
Generated
Columns
Technical leadership & vision
Market leadership
Innovation and consolidation
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Quick Deploy
Solution Design
Migration Assessment
Migration Assistance
PostgreSQL Strategy
Security Assessment
Enterprise Architecture
EDB Postgres Advanced Server
PostgreSQL
EDB Postgres Tools*
PostgreSQL Optimization Enterprise Strategy Custom Services
Getting Started
Cloud
DBA Service
Remote
DBA Service
Technical
Account Manager
PostgreSQL
Technical Support
Softwar
e
Support
Design
and Build
Services
EDB Software, Support, and Services
Performance Tuning
Automation Services
Monitoring Best Practices
Backup Best Practices
Implementation
Embedded Expert
Training
10. What is the
challenge?
• How to get the most mileage out
of the best open source
relational database
• How do leaders do it?
• Where do they start?
• How do they drive the change?
11. Proven
Practices
● Understand the application
landscape and the fit for
PostgreSQL
● Understand how to eat the
elephant - one byte at a time
● Foster collaboration to drive
adoption
● Use standardization to enable
automation
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Open Source wins in the RDBMS space
By 2022, more than 70% of new in-house applications will be developed on an OSDBMS or
OSDBMS-based dbPaaS, and 50% of existing proprietary RDBMS instances will have been
converted or be in process of converting.
By 2022, more than 60% of all global organizations will formalize their management of internal skills
and standards related to OSDBMS to enable better use of open source in production.
Gartner Group - State of the Open-Source DBMS Market, 2019
13. PostgreSQL won!
If you bet… you bet on PostgreSQL
Most Loved Database
Most Commonly Used Database Postgres Popularity
Source: Stack Overflow Developer Survey, 2020 Source: DB-Engines.com, 2020
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Postgres is second
most popular image
in containers (after
Nginx)
Source: Datadog, Nov 2019, https://www.datadoghq.com/container-report/
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100 TB+; read-only;
relational +; multiple
topics; rel. Integrity
not relevant ; data
scientist focus
Hadoop,
Cassandra
Data volume and
velocity
Where PostgreSQL Shines
Data Lake
Data
Warehouse
Data Mart ODS
System of
Record
System of
Engagement
Edge
Computing
Mobile
Computing
50TB+; read
only; relational;
star/cube/mat.
view; periodic
refresh; multiple
topics; analyst
focused
10TB+; read only;
relational;
star/cube/mat.
view; periodic
refresh; single
topic; citizen
analyst focus
10TB+; read only;
relational only;
normalized data
model; concurrent
refresh; citizen
analyst focused
1-20TB;
read/write; 90%
relational; ACID;
ERP/CRM, Line
of business
focused
< 2TB; read/write;
relational + doc +
GIS; ACID or
BASE; micro
services; website
and social media
focus
< 2TB;
read/write;
relational + doc +
GIS; ACID or
BASE; micro
services; M2M,
IoT focus
< 1GB;
read/write;
relational + doc
+ GIS; single
user; micro
services IoT,
mobile app focus
Redshift,
Snowflake,
Teradata, Exadata,
BigQuery
Exadata, Oracle
DB, SQL Server,
Postgres
Oracle, SQL
Server, Postgres
Oracle, SQL
Server, Postgres
MongoDB,
MySQL, Redis,
Postgres,
MySQL, Postgres SQLite, Realm
Innovation; cost;
compatibility; no
vendor lock in;
Multi-model;
innovation; cost;
Available Evrywhr
Hardware
acceleration;
MPP; S3
integration
Hardware
failover
Native write
scalability
No single user
footprint; no
replication from/to
mobile
Multi-model;
innovation; cost;
Available Evrywhr
Analytics capab.;
compatibility;
heterogeneous rep.
Analytics capab.;
compatibility; ease
of integration.
Description
Key players
PostgreSQL Strengths
PostgreSQL Limitations
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Emerging
• Getting started with PostgreSQL
• Often for a single project
• For test/dev apps
Strategic
• PostgreSQL considered a “standard”
• Many production apps incl. tier 1
• Concerns for scalability, HA, and automation
Expanding
• Increasingly for production apps
• Tools and automation important
• Worries about database security
Your PostgreSQL journey
PostgreSQL Maturity
Where are you?
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Eat the elephant - one byte at a time
Temptation:
● Go for major impact
● Address the worst legacy problem first
Recipe for success:
● Tier your applications
● Develop reference architectures
● Understand your maturity
● Find the balance between feasible and meaningful
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Sample Tiering Framework
RPO: 24 hours
RTO: 24 hours
GRO: NA
DB Failover time: NA
An. maint. window: 24
hours
SLA: 99.5%
RPO: 1 min
RTO: <1 min
(Failover)
6 hours
(PITR)
GRO: NA
DB Failover time: <1 min
An. maint. window: 6 hours
SLA: 99.99%
RPO: No data loss
RTO: <1 min
(Failover)
< 3
hours (PITR)
GRO: 1 min
DB Failover time: <1 min
An. maint. window: 4 hours
SLA: 99.999%
RPO: No data loss
RTO: <1 min
(Failover)
< 3
hours (PITR)
GRO: 1 min
DB Failover time: <1 min
An. maint. window: 4 hours
SLA: 99.999%
RPO: No data loss
RTO: <1 min
(Failover)
< 3
hours (PITR)
GRO: 1 min
DB Failover time: <1 min
An. maint. window: 4 hours
SLA: 99.999%
Departmental
Departmental
Mission Critical
Enterprise
Mission Critical
Enterprise
Mission Critical
High Volume
Enterprise
Mission Critical
High Volume &
High Scale
< 1TB; < 500 TPS; <
100 users
< 1TB; < 500 TPS; <
100 users
< 5TB; < 5000 TPS; <
1000 users
< 5TB; < 10,000 TPS;
< 1000 users
< 20TB; < 10,000
TPS; > 1000 users
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Reference Architectures
● CPU, Memory, Storage
● Local, metro, geo-distributed
● Replicas for redundancy, read-
scalability or both
● Streaming replication, logical
replication or both?
● Connection pooling, query
routing, or both?
● SLA, RPO, RTO, GRO
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On K8s; Why EDB?
Our Operators Our Experience
Most experienced
Kubernetes and PostgreSQL staff
in the market
Operators will utilize
industry standards and
operator frameworks
Our Images
Container images will align
with Cloud Native principles
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On K8s; Design Principles
Solicit feedback from
customers, sales and the
field in all regions to
help identify gaps.
Focus on capabilities that
customers need rather
than a current tool or
implementation to deliver.
Utilize DevSecOps including
industry best practices,
end to end testing processes, and
structured release strategy.
Capability
Focused
Technical
Foundation
Continuous
Improvement
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Orchestrate &
Manage Deployments
Flexibility & Speed
PostgreSQL on multiple clouds using containers, Kubernetes operators, or VM's
Standardize and automate deployments with our deployment scripts
Pay as you go with EPAS as a DBaaS from Alibaba Cloud or IBM Cloud
run EPAS on the major cloud vendors’ cloud compute infrastructure
Cloud &
PostgreSQL Expertise
On-demand DBAs to manage and monitor PostgreSQL with our Cloud DBA Service
Benefits of Choosing EDB for Multi-Cloud Workloads
At EDB we have a multi-cloud strategy focused on enabling customers to deploy anywhere
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Self-managed
Containerized
Postgres technology for the enterprise
EDB Postgres Advanced Server
Oracle compatibility: PL/SQL, 26 native packages,
hints, password profiles, OCI/JDBC/ODBC/.NET
drivers; Security; Manageability
High Availability
Streaming replication,
logical replication, near-
zero downtime operation
Management
Database
development,
monitoring, alerting,
management by
exception
Integration
Replication from/to 3rd
party; FDW/SQL MED;
geo-distributed
replication
Migration
Schemas, stored
procedures, data,
snapshot migration,
change data capture
Virtualized
Managed
Alibaba DBaaS
EDB DBaaS
Bare Metal
PostgreSQL
ACID compliant; MVCC; object relational;
extensible; scalable; reliable
Technology Platforms
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Collaboration and evangelizing
Problem Evangelizing Enablement
Successful open source adoption benefits from organizational change
● DBA teams and
development teams are
often at arms length
● “The infrastructure is
ready, but nobody uses it”
● “We would build on
Postgres, but the DBAs
can’t handle it”
● Create a bottom-up
innovation movement
● Informal discussions,
lunch & learns,
hackathons, meetups
● Create DevOps culture -
break down the walls
between developers
and DBAs
● Make sure DBAs are
ready to support
production
● Consider Remote DBA
Services
● Invest in automation to
be responsive
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Postgres Deployment Automation
Technology Decision
Choices
• Terraform
• CloudFormation *
• Ansible
• Chef
• Puppet
• Salt
• Configuration Management vs Provisioning
• Procedural vs Declarative
• With local install or not
• Mutable vs Immutable Infrastructure
• Agent vs Agentless
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Recommended Practices
• Understand the application landscape and the fit
for PostgreSQL
• Understand how to eat the elephant - one byte at a
time
• Foster collaboration to drive adoption
• Use standardization to enable automation
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Resources
Thank You
Next Webinar: March 2
Remote DBA Service: Powering your DBA needs
The EDB Website
Postgres
A Strategic Weapon
Reference Architectures
Ansible Galaxy
Postgres Roles