Migrating Oracle Databases To Cassandra

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1 BY UMAIR MANSOOB

2 Why Cassandra Lower Cost of ownership makes it #1 choice for Big Data OLTP Applications. Unlike Oracle, Cassandra can store structured, semi-structured, and unstructured data. Cassandra is the right choice when you need availability and performance at scale, normally costs % less than just Oracle s enterprise edition alone. Oracle is not architected to tackle the new wave of big data, online applications developed today Provide continuous availability with redundancy in both data and function across one or more locations/ Data Centers vs. simple failover for the Oracle database. Can handle high velocity data coming in via sensors, mobile devices, and the like, and have extreme right speed and low latency query speed. Support all types of workload without needing to ETL data in different data model. Built-in data compressed up to 80% without performance overhead.

3 Who s Using Cassandra

4 Comparing Cost Oracle vs Cassandra Above cost combine with lack of support for unstructured Data can be no brainer for many companies

5 Comparing with Other NoSQL Databases

6 Cassandra Architecture

7 Oracle vs Cassandra Name Oracle Cassandra Database Schema s Yes Schema Free Secondary Indexes Yes Limited SQL Yes CQL ( DDL, DML) Db Scripting Yes ( PL/SQL) No Partitioning Methods Horizontal Partitioning Sharding Consistency Immediate Eventual / Immediate Concurrency Yes Yes Durability Yes Yes Multi-DataCenter Capabilities No Yes Data Consistency Model CAP Theorem ACID Data Compression Various Types of compression Built-in Data modeling 3 rd Normal Form 1 st or 2 nd Normal Form

8 When Cassandra Is not Right ACID-compliant transactions, with nested transactions, commits/rollbacks, and full referential integrity required If you cannot avoid join operations and you cannot code join using programs. If you application only has structured data, No even semi unstructured data is needed. When application load is in the range of low medium, where MYSQL might be a better choice. No requirement for a single database/cluster to span many different data centers. High availability requirements can be accomplished via a synchronous replication architecture that is primarily maintained at a single data center.

9 CAP vs ACID consistency CAP stands for "consistency, availability, and partition tolerance. The CAP theorem, states that, at most, only two of these properties can obtain in any shareddata system ACID (atomicity, consistency, isolation, durability) properties of a traditional relational database management system (RDBMS Oracle) ACID consistency is all about database rules. If a schema declares that a value must be unique, then a consistent system will enforce uniqueness. CAP consistency promises that every replica of the same logical value, spread across nodes in a distributed system, has the same exact value at all times.

10 Achieving Data Consistency Data written to a database cluster is first written to a commit log in the same fashion that nearly every popular RDBMS does. Cassandra offers tunable data consistency. This means a developer or administrator can choose how strong they wish consistency across nodes to be. The strongest form of consistency is to mandate that any data modifications be made to all nodes. Cassandra provides consistency in the CAP sense, in that all readers will see the same values. Cassandra supports different type of consistency models (Strict consistency, Causal consistency, Eventual consistency).

11 Data Modeling Best Practices Don t optimize your data model to minimize the Writes, they are cheap in Cassandra. Don t optimize your data model to minimize Data duplication, duplication is good for efficient reads. Focus on spread data evenly around the cluster by picking good primary key for table. Focus on minimizing number of partition reads, ideally 1 partition per read because each partition might reside in different nodes. The way to minimize partition reads is to model your data to fit your queries. In General you will use roughly one table per query pattern. If you need to support multiple query patterns, you usually need more than one table. Remember, data duplication is okay. Many of your tables may repeat the same data.

12 Migrating Data to Cassandra Using Cassandra s High-Speed Loader : Data from Oracle can be extracted into flat files that are delimited in some way and then loaded into Cassandra tables via the CQL COPY command. Using Sqoop : DataStax Enterprise supports Sqoop, which is a utility designed to transfer data directly from an RDBMS like Oracle into Cassandra Pentaho s Data Integration product call Kettle with a free community edition. Use Spark to Load Oracle Data into Cassandra. ETL tools - there are a spread of ETL equipment (e.g. Informatica) that aid Cassandra as both a supply and goal facts platform.

13 What parts of an Oracle database cannot be migrated Cassandra Stored procedures Views Triggers Functions Security privileges Referential integrity constraints Rules Partitioned table definitions

14 Thank You