This document compares different NoSQL database options and discusses which type may be best for different use cases. It provides an overview of the current NoSQL landscape and models, including key-value, document, graph and wide column stores. Specific databases like Redis, CouchBase, Neo4j and Cassandra are compared based on features like query support, operations, and commercial options. The document recommends choosing a database based on the specific problem and considering aspects like data size, read/write needs, and tradeoffs between consistency, availability and partitioning. It also advocates starting small but with significance and considering hybrid SQL/NoSQL approaches.

1. NoSQL Options Compared Different Horses for Different Courses

2. NoSQL Options Compared Different Horses for Different Courses The current world of NoSQL The NoSQL model NoSQL classes Which model should you use Best use (& use cases comparison) Choosing the Right Horse Lessons learned from actual use

3. The current world of NoSQL The current world of NoSQL RDBMS 105+ databases NoSQL 122+ databases Forecast NoSQL market expected to reach $3.4 Billion by 2018 NoSQL market revenue $14 Billion over 2013 – 2018 RDBMS are great and ... will be fine

4. Recap: RDBMS are great SQL ACID Well understood by developers Well supported by frameworks and tools Backups Tuning Recovery support

5. RDBMS are great, but... Difficult to handle relational schema Schema changes Difficult to scale writes Vertical scaling is limited Horizontal scaling is limited

6. Bridging NoSQL\SQL divide Interest in using NoSQL technology has reemerged: Oracle released MySQL + NoSQL memcached plugin More: Neo4J announced JDBC (SQL) driver Cassandra + CQL CouchBase + UnQL

7. NoSQL model promotes Schema-free approach Flexible data models No unneeded complexity Strict data consistency might be unnecessary Big data amount H igh throughput Over RDBMS expensive in performance BASE (not ACID) Eventually consistent Simple API

8. NoSQL models 31% Key Value 10% Document 13% Graph 9% Column Family 6% XML 10% Object 21% Other

9. NoSQL models Column Oriented Store - each storage block contains data from only one column Document Store - stores documents made up of tagged elements Key Value Store - hash table of keys Graph Database - stores data in the nodes and relationships of a graph

10. NoSQL candidates to compare Key Value / Tuple Store Document Store Graph Database Wide Column Store / Column Families Database Redis open source networked in-memory key-value optional durability written in ANSI C CouchBase open source high-performance map/reduce schema-free document-oriented written in C, C++, Erlang Neo4j open source embedded or server disk-based transactional d ata stored in graphs written in Java Cassandra open source no single point of failure column family store tunable consistency written in Java

11. Comparison General Information Redis CouchBase Neo4j Cassandra Language C C, C++, Erlang Java Java Commercial Support Third party companies Consulting & Support with Enterprise Neo4j Advanced, Neo4j Enterprise DataStax, Impetus, Acunu, Riptapo, Cubet Technologies Customers GitHub, Guardian Media Group Zynga, AOL, BBC Adobe, Cisco, StudiVZ, Deutsche Telekom, Fanbox Twitter, Digg, Reddit, Rackspace, Facebook Licenses New BSD Community & Enterprise Licenses GPL or AGPLv3 Apache License 2

12. Comparison Queries & Operations Redis CouchBase Neo4j Cassandra Client Libraries Bindings + REST\HTTP non-vBucket or v-Bucket Bindings + REST\HTTP Thrift based C + + n/a + C++ n/a + n/a + C# + + + + Java + + + + Perl + + + + PHP + + n/a + Python + + + + Ruby + + + + Querying - - - - Secondary Indexes n/a + - + Map/Reduce n/a n/a n/a Hadoop supported ACID transactions n/a + + +/- (tunable consistency)

13. Best Use Redis CouchBase Neo4j Cassandra Real-time systems where low latency is critical (games) Syncing online and offline data (allows synchronization and sharing of data and applications across multiple platforms and mobile devices) Cloud/network management Managing large streams of non-transactional data: apache logs, application logs, etc High performance caching tier for web sites and other applications Social and online gaming Social, geospatial data Consistent, fast response times under writes (high volume writes) Server for backed sessions or transient data Data management layer for recommendation engine Bioinformatics Real-time analytics & statistics Service offering some real-time statistics Highly available solution

14. Which model should you use? Column Oriented Store Document Store Key Value Store Graph Database More specific: which NoSQL database?

15. Answer This depends on your case! Compare your problems to others Evaluate characteristics of NoSQL storage: Maturity Connectivity/Querying/Operations

16. More aspects to consider How big is your data Massive read/write throughput Fast key-value access No single point of failure Tunable Brewer's CAP trade-offs: Consistency Availability Partition Tolerance Maintainability, Administration

17. Lessons learned from actual use Start small, but significant Is not “one size fits all”, but “horses for courses” Consider a Hybrid Approach (NoSQL + RDBMS)

18. Lessons learned from actual use Hybrid Approach NoSQL RDBMS Business Facade Two Databases: NoSQL + RDBMS Key Value Storage for Session Data + RDBMS for User Data Column Storage for Reporting Data + RDBMS for User Data

19. Q&A Thank you for attention mail: [email_address] skype: siarhei_bushyk