NoSQL Databases Oracle - Berkeley DB

1. NoSQL DatabasesOracle - Berkeley DB

2. Content • A brief intro to NoSQL • About Berkeley Db • About our application

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4. What is NoSQL? • Stands for Not Only SQL • Class of non-relational data storage systems • Usually do not require a fixed table schema nor do they use the concept of joins, group by, order by and so on. • All NoSQL offerings relax one or more of the ACID properties.

5. What is NoSQL ? • Next generation databases • Characteristic: • Large Data Volumes • Non-relational • Distributed • Open-source • Scalable replication and distribution

6. CAP Theorem

7. History of NoSQL • The term NoSQL was introduced by Carl Strozzi in 1998 to name his file based database. • It was again re-introduced by Eric Evans when an event was organized to discuss open source distributed databases. 8

8. Why NoSQL Databases ? • Bigness • Massive write performance • Fast key-value access • Flexible schema and Flexible data types • No single point of failure • Programming ease of use

11. Scaling to size vs complexity. 12

14. Berkeley DB - Introduction • An open-source, embeddedtransactionaldata management system. • A key/value store. • Runs on everything from cell phone to large servers. • Distributed as a library that can be linked directly into an application. • Berkeley DB has high reliability and high performance.

15. Berkeley DB Product Family Architecture

16. Berkeley DB: The Design Philosophy • Provide mechanisms without specifying policies. • For example, Berkeley DB is abstracted as a store of <key, value> pairs. • Both keys and values are opaque byte-strings. • Berkeley DB has no schema. • Application that embeds Berkeley DB is responsible for imposing its own schema on the data.

17. Data Access Services • Indexing methods • B-Tree • Hash • Queue • A record-number-based index

18. Advantages of <key, value> pairs • An application is free to store data in whatever form is most natural to it. • Objects (like structures in C language) • Rows in Oracle, SQL Server • Columns in C-store • Different data formats can be stored in the same databases.

19. Data Management Services • Concurrency • Transactions • Recovery

20. Berkeley DB Applications • Local Directory Access Protocol • Mail Servers • Manage access control lists • Store user keys in a public-infrastructure • Record machine-to-network address mappings in address servers

24. Berkeley DB for Computationally Intensive Algorithms • Algorithms that repeatedly execute a computationally intensive operation • E.g. Factorial • Useful to create a cache containing the already computed results • Cache = Set of <key,value> pairs containing <n, factorial(n)> • Advantages: • avoid to re-compute results for the same input (even over different executions) • In a process crash, we can still start again the process and quickly go back to the point where it stopped

25. In memory map • Simple • Very efficient (b/s in completely memory) • Need considerable amount of memory • No fault tolerance (We need to manually save data to a file) • Relation Databases • ACID properties may not be necessary • Cannot handle Big data • Slow • NoSQL databases (Berkeley DB) • Fast key-value access • Flexible schema and Flexible data types • Ease of use • Fault tolerance

26. Berkeleydb.java

27. Open Environment: • EnvironmentConfig class specify environment configuration parameters • Open Class Catalog: • Class catalog : specialized database store that contain java class descriptions of all serialized objects stored in the database • Create Database and StoredClassCatalog object

29. Open Database: • Close Environment, Class Catalog and Databases:

30. DBViews.java

31. Factorial.java

36. Factorial (Berkeley DB ) – Memory Usage

37. Factorial (MySQL) – Memory Usage

38. Factorial (HashMap) – Memory Usage