DevCon Summit 2014 #DevelopersUnitePH: The "What" and "Why" of NoSQL by Matias Cascallares, MongoDB
22 likes2,508 views
This document provides an overview of NoSQL databases by telling a story about a company that needed a new database solution to support growing user numbers, data size, and write throughput for a social media aggregation project. It explains that traditional SQL databases may not meet the needs of modern web applications that generate large amounts of structured and unstructured data very quickly. It then gives brief descriptions of different NoSQL database categories including key-value stores, document databases, BigTable databases, and search engines.
DevCon Summit 2014 #DevelopersUnitePH: The "What" and "Why" of NoSQL by Matias Cascallares, MongoDB
- 1. THE “WHAT” AND “WHY” OF NOSQL Matias Cascallares @mcascallares [email protected]
- 2. Who Am I? • Originally from Buenos Aires, Argentina • Solutions Architect @ MongoDB based in Singapore • Software Engineer, most of my experience in web environments • In my toolbox I have Java, Python and Node.js
- 3. Let me tell you a story… • Beginning of 2011 • Tier-1 hardware manufacturer wanted to build a social aggregator backend • Supported platforms: Twitter, Facebook and blogs (RSS/Atom) • We were a MySql shop
- 4. That moment! Based on estimations: - # of users - dataset size - write throughput …we had some doubts
- 5. The Expert
- 6. NoSQL
- 7. Not Only SQL
- 8. Why do we need to look for new databases?
- 11. Some facts of our age • 3M of emails sent per second • 20 hs of video uploaded to YouTube p/min • 75 products ordered on Amazon p/sec • 100K new tweets per minute
- 12. Structured Data
- 13. Structured Data Unstructured Data
- 15. SAY BIG DATA ONE MORE TIME
- 20. .. and not so long time ago
- 21. Hardware nowadays HTTP POST https://ec2.amazonaws.com/? Action=StartInstances &InstanceId.1=i-10a64379 &AUTHPARAMS
- 24. NoSql Families • Key-value stores • Document databases • BigTable • Search engines
- 25. Key-value stores • Access only by primary key • Implementations are mainly in memory • Insanely fast • Value is "something" like a BLOB
- 26. Document databases • General purpose data storage • Dynamic schema / unstructured data • Flexible query & indexing capabilities • Consistent writes • Aggregation capabilities
- 27. BigTable • Multidimensional sorted maps • Data stored across a ring of nodes (P2P) • Eventually consistent based on quorum • Append only storage • Fast when writing, not so fast when reading.
- 28. Search engines • Not used as primary storage • Full-text search capabilities • Faceted search • Lightweight integration with REST APIs
- 30. Thanks!