Postgres NoSQL - Delivering Apps Faster
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The document discusses the capabilities of PostgreSQL as a NoSQL and SQL integration platform for enterprises, emphasizing its performance, data management flexibility, and support for various data types, including JSON and hstore. It highlights that PostgreSQL can handle large volumes of unstructured data while maintaining ACID compliance, challenging common misconceptions about NoSQL databases. It also presents performance benchmarks comparing PostgreSQL with MongoDB and describes its features like foreign data wrappers (FDW) for seamless data integration across different databases.
Postgres NoSQL - Delivering Apps Faster
- 1. © 2014 EnterpriseDB Corporation. All rights reserved. 1 Postgres NoSQL - Delivering Applications Faster Marc Linster – SVP, Products and Services
- 2. © 2014 EnterpriseDB Corporation. All rights reserved. 2 • EDB Introduction • BigData and NoSQL: Volume, Variety and Velocity • Postgres – NoSQL for the Enterprise • Performance Evaluation – Phase 2 • FDW – Coexistence of NoSQL only and SQL • Leveraging a proven skill set to create Web 2.0 applications • Postgres as a NoSQL/SQL Integration Platform Agenda
- 3. © 2014 EnterpriseDB Corporation. All rights reserved. 3 POSTGRES innovation ENTERPRISE reliability 24/7 support Services & training Enterprise-class features & tools Indemnification Product road-map Control Thousands of developers Fast development cycles Low cost No vendor lock-in Advanced features Enabling commercial adoption of Postgres
- 4. © 2014 EnterpriseDB Corporation. All rights reserved. 4 Postgres Plus Advanced Server Postgres Plus Cloud Database High Availability PerformanceManagement REMOTE DBA 24x7 SUPPORT PROFESSIONAL SERVICES TRAINING EDB Serves All Your Postgres Needs PostgreSQL Security
- 5. © 2014 EnterpriseDB Corporation. All rights reserved. 5 • Common Myth (or misconception) − Volume, Velocity, Variety and ACID are not compatible! − You cannot have it all! • Their (incorrect) reasoning: − Very High Data Volumes (log analysis, append only applications, social media) applications cannot be handled by relational systems − The data is sent to the application at high speeds and has to be ingested quickly – not in batch mode − Web 2.0 applications require more than SQL – they also need documents, IMs, emails, graphs, links − ACID (Atomicity, Consistency, Isolation and Durability) compliant systems are too inflexible, too slow and cannot handle the new data types BigData, NoSQL and SQL: Myths about Volume, Variety, Velocity and ACID
- 6. © 2014 EnterpriseDB Corporation. All rights reserved. 6 $$$$$$ ACID, Volume, Velocity and Variety in Context ACID Transactional Ingestion Velocity Variety Data Volume Postgres Data Mining/BigData Document/NoSQL- Only
- 7. © 2014 EnterpriseDB Corporation. All rights reserved. 7 • Performance Benchmarks − Postgres is very fast and can handle huge amounts of data − Postgres can selectively relax key ACID features to increase performance • Data Types − Postgres has JSON, JSONB, Key-Value Pair, plus arrays, ranges, timezones, dates, integer, floating point, etc. • Proven track record − ACID compliant − Open source − ANSI SQL − Huge developer and vendor community Postgres – NoSQL for the Enterprise
- 8. © 2014 EnterpriseDB Corporation. All rights reserved. 8 • HSTORE − Key-value pair − Simple, fast and easy − Postgres v 8.2 – pre-dates many NoSQL-only solutions • JSON − Hierarchical document model − Introduced in Postgres 9.2, perfected in 9.3 • JSONB − Binary version of JSON − Faster, more operators and even more robust − Postgres 9.4 NoSQL Data in Postgres
- 9. © 2014 EnterpriseDB Corporation. All rights reserved. 9 • Creating a table with a JSONB field CREATE TABLE json_data (data JSONB);! • Simple JSON data element: {"name": "Apple Phone", "type": "phone", "brand": "ACME", "price": 200, "available": true, "warranty_years": 1}! • Inserting this data element into the table json_data INSERT INTO json_data (data) VALUES ! !(’ { !"name": "Apple Phone", ! ! !"type": "phone", ! ! !"brand": "ACME", ! ! !"price": 200, ! ! !"available": true, ! ! !"warranty_years": 1 ! !! !} ')! JSON Examples
- 10. © 2014 EnterpriseDB Corporation. All rights reserved. 10 SELECT DISTINCT ! !data->>'name' as products ! FROM json_data; ! products ! ------------------------------! Cable TV Basic Service Package! AC3 Case Black! Phone Service Basic Plan! AC3 Phone! AC3 Case Green! Phone Service Family Plan! AC3 Case Red! AC7 Phone! A simple query for JSON data This query does not return JSON data – it returns text values associated with the key ‘name’
- 11. © 2014 EnterpriseDB Corporation. All rights reserved. 11 SELECT data FROM json_data;! data ! ------------------------------------------! {"name": "Apple Phone", "type": "phone", "brand": "ACME", "price": 200, "available": true, "warranty_years": 1}! A query that returns JSON data This query returns the JSON data in its original format
- 12. © 2014 EnterpriseDB Corporation. All rights reserved. 12 • JSON is naturally integrated with ANSI SQL in Postgres • JSON and HSTORE are elegant and easy to use extensions of the underlying object- relational model • JSON and SQL queries use the same language, the same planner, and the same ACID compliant transaction framework JSON and ANSI SQL – A Great Fit
- 13. © 2014 EnterpriseDB Corporation. All rights reserved. 13 SELECT DISTINCT product_type, data->>'brand' as Brand, data->>'available' as Availability FROM json_data JOIN products ON (products.product_type=json_data.data->>'name') WHERE json_data.data->>'available'=true; product_type | brand | availability ---------------------------+-----------+-------------- AC3 Phone | ACME | true JSON and ANSI SQL Example ANSI SQL JSON No need for programmatic logic to combine SQL and NoSQL in the application – Postgres does it all
- 14. © 2014 EnterpriseDB Corporation. All rights reserved. 14 Bridging between SQL and NoSQL Simple ANSI SQL Table Definition CREATE TABLE products (id integer, product_name text );! Select query returning standard data set SELECT * FROM products; ! id | product_name ! ----+--------------! 1 | iPhone! 2 | Samsung! 3 | Nokia! Select query returning the same result as a JSON data set SELECT ROW_TO_JSON(products) FROM products; {"id":1,"product_name":"iPhone"} {"id":2,"product_name":"Samsung"} {"id":3,"product_name":"Nokia”}
- 15. © 2014 EnterpriseDB Corporation. All rights reserved. 15 • Start unstructured, and become structured as you learn more − Use the quick-to-get-started capabilities of NoSQL − Complete the initial sprints without a DBA − Move data between unstructured and structured − Embrace corporate data standards as you move from the stand-alone application towards integrated applications with a bigger value proposition Postgres Provides Great Flexibility By 2017, 50% of data stored in NoSQL DBMSs will be damaging to the business due to lack of applied information governance policies and programs. Gartner, December 2013
- 16. © 2014 EnterpriseDB Corporation. All rights reserved. 16 • Goal − Help our customers understand when to chose Postgres and when to chose a specialty solution − Help us understand where the NoSQL limits of Postgres are • Setup − Compare Postgres 9.4 to Mongo 2.6 − Single instance setup on AWS M3.2XLARGE (32GB) • Test Focus − Data ingestion (bulk and individual) − Data retrieval Postgres NoSQL Performance Evaluation Load Generator Postgres 9.4 MongoDB 2.6
- 17. © 2014 EnterpriseDB Corporation. All rights reserved. 17 Postgres NoSQL Performance Evaluation Generate JSON Documents 10 M documents & 50 M documents Load into MongoDB 2.6 (IMPORT) Load into Postgres 9.4 (COPY) 10 Million individual INSERT commands 10 Million individual INSERT commands Multiple SELECT statements Multiple SELECT statements T1 T2 T3
- 18. © 2014 EnterpriseDB Corporation. All rights reserved. 18 Test 1: 10 Million Documents Test Criterion MongoDB 2.6 Postgres 9.4 Data load (s) 2,624 1,193 Inserts (s) 16,491 5,637 Selects (s) 187 67 DB Size (GB) 20.05 14.89 0% 50% 100% 150% 200% 250% 300% 350% Data load (s) Inserts (s) Selects (s) DB Size (GB) Mongo DB 2.4/Postgres 9.4 Rela9ve Performance Comparison (10M Documents) MongoDB 2.6 Postgres 9.4
- 19. © 2014 EnterpriseDB Corporation. All rights reserved. 19 Test 2: 50 Million Documents Test Criterion MongoDB 2.6 Postgres 9.4 Data load (s) 15,391 7,319 Inserts (s) 85,639 29,125 Selects (s) 1,929 753 DB Size (GB) 92.63 69.36 0% 50% 100% 150% 200% 250% 300% 350% Data load (s) Inserts (s) Selects (s) DB Size (GB) Mongo DB 2.4/Postgres 9.4 Rela9ve Performance Comparison (50M Documents) MongoDB 2.6 Postgres 9.4
- 20. © 2014 EnterpriseDB Corporation. All rights reserved. 20 • Tests confirm that Postgres can handle many NoSQL workloads • EDB is making the test scripts publically available • EDB encourages community participation to better define where Postgres should be used and where specialty solutions are appropriate • Download the source at https://github.com/EnterpriseDB/pg_nosql_benchmark • Join us to discuss the findings at http://bit.ly/EDB-NoSQL-Postgres-Benchmark Postgres NoSQL Performance Evaluation
- 21. © 2014 EnterpriseDB Corporation. All rights reserved. 21 • FDW implements SQL/MED ("SQL Management of External Data") • PostgreSQL 9.1 - read-only support • PostgreSQL 9.3 – read/write support • FDW − Makes data on other servers (or services) look like tables in Postgres − available for databases (MongoDB, MySQL, Oracle, …), files, services (Twitter, …) • MongoDB FDW: https://github.com/EnterpriseDB Foreign Data Wrappers – Co-Existence Platform
- 22. © 2014 EnterpriseDB Corporation. All rights reserved. 22 CREATE EXTENSION mongo_fdw;! CREATE SERVER mongo_server !FOREIGN DATA WRAPPER mongo_fdw !OPTIONS (address '172.24.39.129', port '27017');! CREATE USER MAPPING FOR enterprisedb !SERVER mongo_server !OPTIONS (username 'mongo', password 'mongo');! CREATE FOREIGN TABLE mongo_data( !name text, !brand text, !type text) !SERVER mongo_server !OPTIONS ( ! !database 'benchmark', ! !collection 'json_tables');! MongoDB FDW Example
- 23. © 2014 EnterpriseDB Corporation. All rights reserved. 23 SELECT * FROM mongo_data WHERE brand='ACME' limit 10;! ! name | brand | type -------------+-------+------- AC7553 Phone | ACME | phone AC7551 Phone | ACME | phone AC7519 Phone | ACME | phone AC7565 Phone | ACME | phone AC7555 Phone | ACME | phone AC7529 Phone | ACME | phone AC7528 Phone | ACME | phone AC7547 Phone | ACME | phone AC7587 Phone | ACME | phone AC7541 Phone | ACME | phone! (10 rows)! ! MongoDB FDW Example
- 24. © 2014 EnterpriseDB Corporation. All rights reserved. 24 INSERT INTO mongo_data(name, brand, type) !VALUES('iphone6 phone','Apple Inc','phone');! SELECT* FROM mongo_data WHERE brand='Apple Inc';! _id | name | brand | type --------------------------+----------------+-----------+------- 53ea4f59fe5586a15714881d | iphone6 phone | Apple Inc | phone! ! UPDATE mongo_data SET brand='Apple Product' !WHERE brand='Apple Inc’;! SELECT * FROM mongo_data WHERE brand='Apple Product’;! _id | name | brand | type --------------------------+----------------+---------------+------- 53ea4f59fe5586a15714881d | iphone6 phone | Apple Product | phone! ! MongoDB FDW Example
- 25. © 2014 EnterpriseDB Corporation. All rights reserved. 25 • Postgres allows you to − Use the same Infrastructure DBAs (no change!!!) − Use the same management, maintenance, backup, restore, high availability, disaster recovery and compliance processes for SQL and NoSQL − Start unstructured and align with corporate governance standards as your project matures − Start unstructured (data logic in the application) and migrate shared data logic into the database è enhances reuse − Build on the existing PL/pgSQL programming skillset − EDB Postgres Plus adds Oracle PL/SQL compatibility (fully integrated with JSON and HSTORE) Leveraging a Proven Skill Set
- 26. © 2014 EnterpriseDB Corporation. All rights reserved. 26 • Postgres has many NoSQL features without the drawbacks: − Schema-less data types, with sophisticated indexing support − Schema changes with rapid addition and removal of keys and tags − Durable by default, but configurable per-table or per-transaction − Foreign Data Wrappers (FDW) support co-existence and tight integration − Standards based with very low technology risk − Highly available skill set Postgres: The Best of Both Worlds
- 27. © 2014 EnterpriseDB Corporation. All rights reserved. 27 • Structures and standards emerge! • Data has references (products link to catalogues; products have bills of material; components appear in multiple products; storage locations link to ISO country tables) • When the database has duplicate data entries, then the application has to manage updates in multiple places – what happens when there is no ACID transactional model? “No SQL Only” or “Not Only SQL”?
- 28. © 2014 EnterpriseDB Corporation. All rights reserved. 28 • Postgres is Not Only SQL (NoSQL is No SQL only) • Fully ACID compliant • Proven track record • Fully capable of handling the variety, velocity and volume requirements of most applications • Tackle NoSQL projects without leaving the capabilities of the relational model behind you Postgres is the best of both worlds, and it’s open source! Say ‘Yes’ to ‘Not Only SQL’
- 29. © 2014 EnterpriseDB Corporation. All rights reserved. 29 • Contact us for an Enterprise NoSQL Assessment ([email protected]) • Review EDB’s NoSQL Resources − Whitepaper - http://www.enterprisedb.com/wp-using-nosql-features-postgres − NoSQL Solution Information - http://www.enterprisedb.com/nosql-for-enterprise − Benchmarks- https://github.com/EnterpriseDB
- 30. © 2014 EnterpriseDB Corporation. All rights reserved. 30
- 31. © 2014 EnterpriseDB Corporation. All rights reserved. 31