Apache Cassandra

Releases after graduation include

• 0.6, released Apr 12 2010, added support for integrated caching, and Apache Hadoop MapReduce[8]
• 0.7, released Jan 08 2011, added secondary indexes and online schema changes[9]
• 0.8, released Jun 2 2011, added the Cassandra Query Language (CQL), self-tuning memtables, and support for zero-downtime upgrades[10]
• 1.0, released Oct 17 2011, added integrated compression, leveled compaction, and improved read-performance[11]
• 1.1, released Apr 23 2012, added self-tuning caches, row-level isolation, and support for mixed ssd/spinning disk deployments[12]
• 1.2, released Jan 2 2013, added clustering across virtual nodes, inter-node communication, atomic batches, and request tracing[13]
• 2.0, released Sep 4 2013, added lightweight transactions (based on the Paxos consensus protocol), triggers, improved compactions
• 2.1 released Sep 10 2014[14]
• 2.2 released July 20, 2015
• 3.0 released November 11, 2015
• 3.1 through 3.10 releases were monthly releases using a tick-tock-like release model, with even-numbered releases providing both new features and bug fixes while odd-numbered releases will include bug fixes only.[15]
• 3.11 released June 23, 2017 as a stable 3.11 release series and bug fix from the last tick-tock feature release.
• 4.0 released July 26, 2021.
• 4.0.1 released September 7, 2021.
• 4.0.2 released February 8, 2022.
• 4.0.3 released February 17, 2022.
• 4.0.4 released May 13, 2022.
• 4.0.5 released July 18, 2022.
• 4.0.6 released August 25, 2022.
• 4.0.7 released October 23, 2022.

Cassandra introduced the Cassandra Query Language (CQL). CQL is a simple interface for accessing Cassandra, as an alternative to the traditional Structured Query Language (SQL). CQL adds an abstraction layer that hides implementation details of this structure and provides native syntaxes for collections and other common encodings. Language drivers are available for Java (JDBC), Python (DBAPI2), Node.JS (Datastax), Go (gocql) and C++.[21]

The keyspace in Cassandra is a namespace that defines data replication across nodes. Therefore, replication is defined at the keyspace level. Below an example of keyspace creation, including a column family in CQL 3.0:[22]

CREATE KEYSPACE MyKeySpace
  WITH REPLICATION = { 'class' : 'SimpleStrategy', 'replication_factor' : 3 };

USE MyKeySpace;

CREATE COLUMNFAMILY MyColumns (id text, lastName text, firstName text, PRIMARY KEY(id));

INSERT INTO MyColumns (id, lastName, firstName) VALUES ('1', 'Doe', 'John');

SELECT * FROM MyColumns;

Which gives:

 id | lastName | firstName
----+----------+----------
  1 | Doe      | John

(1 rows)

Up to Cassandra 1.0, Cassandra was not row level consistent,[23] meaning that inserts and updates into the table that affect the same row that are processed at approximately the same time may affect the non-key columns in inconsistent ways. One update may affect one column while another affects the other, resulting in sets of values within the row that were never specified or intended. Cassandra 1.1 solved this issue by introducing row-level isolation.[24]

Cassandra is not supported on Windows as of version 4, see issue CASSANDRA-16171.[25]

Deletion markers called "Tombstones" are known to cause severe performance degradation.[26]

Cassandra is wide column store, and, as such, essentially a hybrid between a key-value and a tabular database management system. Its data model is a partitioned row store with tunable consistency.[19] Rows are organized into tables; the first component of a table's primary key is the partition key; within a partition, rows are clustered by the remaining columns of the key.[27] Other columns may be indexed separately from the primary key.[28]

Tables may be created, dropped, and altered at run-time without blocking updates and queries.[29]

Cassandra cannot do joins or subqueries. Rather, Cassandra emphasizes denormalization through features like collections.[30]

A column family (called "table" since CQL 3) resembles a table in an RDBMS (Relational Database Management System). Column families contain rows and columns. Each row is uniquely identified by a row key. Each row has multiple columns, each of which has a name, value, and a timestamp. Unlike a table in an RDBMS, different rows in the same column family do not have to share the same set of columns, and a column may be added to one or multiple rows at any time.[31]

Each key in Cassandra corresponds to a value which is an object. Each key has values as columns, and columns are grouped together into sets called column families. Thus, each key identifies a row of a variable number of elements. These column families could be considered then as tables. A table in Cassandra is a distributed multi dimensional map indexed by a key. Furthermore, applications can specify the sort order of columns within a Super Column or Simple Column family.