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{{short description|Free and open-source database management system}}
{{External links|date=October 2023}}
{{Use mdy dates|date=September 2024}}
{{Use American English|date=September 2024}}
{{Infobox software
| name = Apache Cassandra
| logo = [[File:Cassandra logo.svg|frameless|Cassandra logo]]
| author = Avinash Lakshman, Prashant Malik / [[Facebook]]
| developer = [[Apache Software Foundation]]
| released = {{Start date and age|2008|07}}
| latest release version = {{wikidata|property|edit|reference|P548=Q2804309|P348}}
| latest release date = {{start date and age|{{wikidata|qualifier|mdy|P548=Q2804309|P348|P577}}}}
| programming language = [[Java (programming language)|Java]]
| operating system = [[Cross-platform]]
| language = English
| genre = [[NoSQL]] [[Database]], [[data store]]
| license = [[Apache License 2.0]]
}}
'''Apache Cassandra''' is a [[free and open-source software|free and open-source]] [[database management system]] designed to handle large volumes of data across multiple [[Commodity computing|commodity servers]]. The system prioritizes availability and [[scalability]] over [[consistency (database systems)|consistency]], making it particularly suited for systems with high write throughput requirements due to its [[Log-structured merge-tree|LSM tree]] indexing storage layer.<ref name="carpenter2022">{{cite book |last1=Carpenter |first1=Jeff |last2=Hewitt |first2=Eben |title=Cassandra: The Definitive Guide |edition=3rd |publisher=[[O'Reilly Media]] |year=2022 |isbn=978-1-4920-9710-5 |pages=}}</ref> As a [[wide column store|wide-column database]], Cassandra supports flexible schemas and efficiently handles data models with numerous sparse columns. The system is optimized for applications with well-defined data access patterns that can be incorporated into the schema design.<ref name="carpenter2022" /> Cassandra supports [[computer cluster]]s which may span multiple [[data center]]s,<ref>{{cite web |access-date=2013-07-25 |first=Joaquin |last=Casares |date=2012-11-05 |publisher=DataStax |title=Multi-datacenter Replication in Cassandra |quote=Cassandra's innate datacenter concepts are important as they allow multiple workloads to be run across multiple datacenters... |url=http://www.datastax.com/dev/blog/multi-datacenter-replication}}</ref> featuring [[Asynchrony (computer programming)|asynchronous]] and masterless replication. It enables [[Latency (engineering)|low-latency]] operations for all clients and incorporates [[Amazon (company)|Amazon]]'s [[Dynamo (storage system)|Dynamo]] [[distributed storage]] and replication techniques, combined with [[Google]]'s [[Bigtable]] data storage engine model.<ref>{{cite web |url=https://cassandra.apache.org/doc/latest/architecture/overview.html |title=Apache Cassandra Documentation Overview |access-date=2021-01-21}}</ref>
== History ==
Avinash Lakshman, a co-author of [[Amazon (company)|Amazon]]'s [[Dynamo (storage system)|Dynamo]], and Prashant Malik developed Cassandra at [[Facebook]] to support the [[inbox]] [[Search engine|search]] functionality. Facebook released Cassandra as open-source software on [[Google Code]] in July 2008.<ref name=JH2008>{{cite web |access-date= 2009-06-04 |date= July 12, 2008 |url= http://perspectives.mvdirona.com/2008/07/12/FacebookReleasesCassandraAsOpenSource.aspx |title= Facebook Releases Cassandra as Open Source |first= James |last= Hamilton}}</ref> In March 2009, it became an Apache Incubator project<ref>{{cite web |date=2009-03-02 |title=Is this the new hotness now? |url=http://www.mail-archive.com/cassandra-dev@incubator.apache.org/msg00004.html |url-status=live |archive-url=https://web.archive.org/web/20100425071855/http://www.mail-archive.com/cassandra-dev%40incubator.apache.org/msg00004.html |archive-date=25 April 2010 |access-date=2010-03-29 |publisher=Mail-archive.com}}</ref> and on February 17, 2010, it graduated to a top-level project.<ref name=GRAD>{{cite web|url=http://www.mail-archive.com/cassandra-dev@incubator.apache.org/msg01518.html |title=Cassandra is an Apache top level project |publisher=Mail-archive.com |date=2010-02-18 |access-date=2010-03-29 |archive-url=https://web.archive.org/web/20100328090322/http://www.mail-archive.com/cassandra-dev%40incubator.apache.org/msg01518.html |archive-date=28 March 2010 |url-status=live }}</ref>
The developers at [[Facebook]] named their database after [[Cassandra]], the [[mythological]] [[Troy|Trojan]] prophetess, referencing her curse of making prophecies that were never believed.<ref>{{cite web |url= http://kellabyte.com/2013/01/04/the-meaning-behind-the-name-of-apache-cassandra/ |archive-url= https://web.archive.org/web/20161101091045/http://kellabyte.com/2013/01/04/the-meaning-behind-the-name-of-apache-cassandra |archive-date= 2016-11-01 |title= The meaning behind the name of Apache Cassandra |access-date= 2016-07-19 |quote= Apache Cassandra is named after the Greek mythological prophet Cassandra. [...] Because of her beauty Apollo granted her the ability of prophecy. [...] When Cassandra of Troy refused Apollo, he put a curse on her so that all of her and her descendants' predictions would not be believed. [...] Cassandra is the cursed Oracle[.] |url-status= dead }}</ref>
== Features and limitations ==
Cassandra uses a [[distributed architecture]] where all nodes perform identical functions, eliminating single points of failure. The system employs configurable replication strategies to distribute data across clusters, providing redundancy and disaster recovery capabilities. The system is capable of linear scaling, which increases read and write throughput with the addition of new nodes, while maintaining continuous service.
Cassandra is categorized as an AP ([[Availability (system)|Availability]] and Partition Tolerance) system, emphasizing availability and partition tolerance over [[Consistency (database systems)|consistency]]. While it offers tunable consistency levels for both read and write operations, its architecture makes it less suitable for use cases requiring strict consistency guarantees.<ref name="carpenter2022" /> Additionally, Cassandra's compatibility with [[Apache Hadoop|Hadoop]] and related tools allows for integration with existing big data processing workflows. Eventual consistency is maintained using [[Tombstone (data store)|tombstones]] to manage reads, [[UPSERT|upserts]], and deletes.
The system's query capabilities have notable limitations. Cassandra does not support advanced query patterns such as multi-table [[Join (SQL)|JOINs]], ad hoc aggregations, or complex queries.<ref name="carpenter2022" /> These limitations stem from its distributed architecture, which optimizes for scalability and availability rather than complex query operations.
== Data model ==
As a [[wide column store|wide-column store]], Cassandra combines features of both key-value and tabular database systems. It implements a partitioned row store model with adjustable consistency levels.<ref name="tunable_consistency">{{cite web |access-date=2013-07-25 |author=DataStax |author-link=DataStax |date=2013-01-15 |title=About data consistency |url=http://www.datastax.com/docs/1.2/dml/data_consistency |archive-url=https://web.archive.org/web/20130726185743/http://www.datastax.com/docs/1.2/dml/data_consistency |archive-date=2013-07-26 |url-status=dead }}</ref> The following table compares Cassandra and [[relational database management systems]] (RDBMS).
{| class="wikitable"
|+ Data Model Comparison: Cassandra vs RDBMS
! Feature !! Cassandra !! RDBMS
|-
| Organization || Keyspace → Table → Row || Database → Table → Row
|-
| Row Structure || Dynamic columns || Fixed schema
|-
| Column Data || Name, type, value, timestamp || Name, type, value
|-
| Schema Changes || Runtime modifications || Usually requires downtime
|-
| Data Model || Denormalized || Normalized with JOINs
|}
The data model consists of several hierarchical components:
===
A keyspace in Cassandra is analogous to a database in [[relational database management system|relational systems]]. It contains multiple tables and manages configuration information, including replication strategy and user-defined types (UDTs).<ref name="carpenter2022" />
=== Tables ===
Tables (formerly called [[Column family|column families]] prior to CQL 3) are containers for rows of data. Each table has a name and configuration information for its stored data. Tables may be created, dropped, or altered at run-time without blocking [[Update (SQL)|updates]] and queries.<ref>{{cite web |access-date=2013-07-25 |first=Jonathan |last=Ellis |date=2012-03-02 |title=The Schema Management Renaissance in Cassandra 1.1 |publisher=DataStax |url=http://www.datastax.com/dev/blog/the-schema-management-renaissance}}</ref>
=== Rows and columns ===
Each row is identified by a [[primary key]] and contains columns. The first component of a table's primary key is the partition key; within a partition, rows are [[Clustered index|clustered]] by the remaining columns of the key.<ref>{{cite web |access-date=2013-07-25 |first=Jonathan |last=Ellis |date=2012-02-15 |title=Schema in Cassandra 1.1 |publisher=DataStax |url=http://www.datastax.com/dev/blog/schema-in-cassandra-1-1}}</ref>
Columns contain data belonging to a row and consist of:
* A name
* A type
* A value
* Timestamp metadata (used for write conflict resolution via "last write wins")
Unlike traditional RDBMS tables, rows within the same table can have varying columns, providing a flexible structure. This flexibility distinguishes Cassandra from relational databases, as not all columns need to be specified for each row.<ref name="carpenter2022" /> Other columns may be indexed separately from the primary key.<ref>{{cite web |access-date=2013-07-25 |first=Jonathan |last=Ellis |date=2010-12-03 |title=What's new in Cassandra 0.7: Secondary indexes |publisher=DataStax |url=http://www.datastax.com/dev/blog/whats-new-cassandra-07-secondary-indexes}}</ref>
== Storage model ==
Cassandra uses a [[Log-structured merge-tree|Log Structured Merge Tree (LSM tree)]] index to optimize write throughput, in contrast to the [[B tree indexing|B-tree indexes]] used by most databases.<ref name="carpenter2022" />
{| class="wikitable"
|+ Storage Model Comparison: Cassandra vs RDBMS
! Feature !! Cassandra !! RDBMS
|-
| Index Structure || LSM Tree || B-Tree
|-
| Write Process || Append-only with Memtable || In-place updates
|-
| Storage Components || Commit Log, Memtable, SSTable || Data files, Transaction Log
|-
| Update Strategy || New entry for each change || Modify existing data
|-
| Delete Handling || Tombstone markers || Direct removal
|-
| Read Optimization || Secondary || Primary
|-
| Write Optimization || Primary || Secondary
|}
The storage architecture consists of three main components:<ref name="carpenter2022" />
===
* '''Commit Log''': A [[Write-ahead logging|write-ahead log]] that ensures write durability
* '''Memtable''': An [[In-memory processing|in-memory]] data structure that stores writes, sorted by primary key
* '''SSTable''' (Sorted String Table): Immutable files containing data flushed from Memtables
=== Write and read processes ===
Write operations follow a two-stage process:
# The write is recorded in the commit log and added to the Memtable
# When the Memtable reaches size or time thresholds, it flushes to an SSTable
Read operations:
# Check Memtable for latest data
# Search SSTables from newest to oldest using bloom filters for efficiency
=== Data management ===
==== Tombstones ====
Every operation (create/update/delete) generates a new entry, with deletes handled via "[[Tombstone (data store)|tombstones]]". While common in many databases, tombstones can cause performance degradation in delete-heavy workloads.<ref>{{cite web |last1=Rodriguez |first1=Alain |title=About Deletes and Tombstones in Cassandra |url=https://thelastpickle.com/blog/2016/07/27/about-deletes-and-tombstones.html |date=27 Jul 2016}}</ref>
==== Compaction ====
Compaction consolidates multiple SSTables to:
* Reduce storage usage
* Remove deleted row tombstones
* Improve read performance
==
Cassandra Query Language (CQL) is the interface for accessing Cassandra, as an alternative to the traditional [[SQL|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 (programming language)|Java]] ([[Java Database Connectivity|JDBC]]), [[Python (programming language)|Python]] (DBAPI2), [[Node.js|Node.JS]] ([[DataStax]]), [[Go (programming language)|Go]] (gocql), and [[C++]].<ref>{{cite web |title=DataStax C/C++ Driver for Apache Cassandra |url=https://github.com/datastax/cpp-driver |access-date=15 December 2014 |work=DataStax}}</ref>
The key space in Cassandra is a namespace that defines data replication across nodes. Therefore, replication is defined at the key space level. Below is an example of key space creation, including a column family in CQL 3.0:<ref>{{cite web |title=CQL |url=https://cassandra.apache.org/doc/cql3/CQL.html |url-status=dead |archive-url=https://web.archive.org/web/20160113141740/http://cassandra.apache.org/doc/cql3/CQL.html |archive-date=13 January 2016 |access-date=5 January 2016}}</ref><syntaxhighlight lang="mysql" line="1">
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;
</syntaxhighlight>
Which gives:
<syntaxhighlight lang="text">
id | lastName | firstName
----+----------+----------
1 | Doe | John
(1 rows)
</syntaxhighlight>
== Distributed architecture ==
=== Gossip protocol ===
Cassandra uses a peer-to-peer gossip protocol for cluster communication. Nodes routinely exchange information about cluster state, including:
* Node availability status
* Schema versions
* Generation timestamps (node bootstrap time)
* Version numbers (logical clock values)
The system uses [[vector clock]]s to track information currency and ignore outdated state data.<ref name="carpenter2022" />
=== Seed nodes ===
The architecture designates certain nodes as "seed" nodes that:
* Bootstrap the cluster
* Serve as guaranteed gossip communication points
* Prevent cluster fragmentation
* Remain discoverable via service discovery methods
This design eliminates single points of failure while maintaining cluster-wide consistency of operational knowledge.<ref name="carpenter2022" />
=== Fault tolerance ===
Cassandra employs the Phi Accrual Failure Detector to manage node failures during cluster operation.<ref>{{cite conference
| title = The Φ Accrual Failure Detector
| first1 = Naohiro | last1 = Hayashibara
| first2 = Xavier | last2 = Défago
| first3 = Rami | last3 = Yared
| first4 = Takuya | last4 = Katayama
| book-title = IEEE Symposium on Reliable Distributed Systems
| year = 2004
| pages = 66–78
| doi = 10.1109/RELDIS.2004.1353004
}}</ref> Through this system, each node independently assesses the availability of other nodes during gossip communication. When a node fails to respond, it is "convicted" and removed from write operations, though it can rejoin the cluster upon resuming heartbeat signals.<ref name="carpenter2022" />
To maintain data integrity during node outages, Cassandra uses a "hinted handoff" mechanism. When writing to an offline node, the coordinator node temporarily stores the write data as a "hint." Once the offline node returns to service, these hints are forwarded to restore data consistency. Notably, Cassandra only permanently removes nodes through explicit administrative decommissioning or rebuilding, preventing temporary communication failures or restarts from triggering unnecessary data rebalancing.<ref name="carpenter2022" />
==Management and monitoring==
Cassandra is a Java-based system that can be managed and monitored via [[Java Management Extensions]] (JMX). The JMX-compliant ''Nodetool'' utility, for instance, can be used to manage a Cassandra cluster.<ref>{{cite web|title=NodeTool|url=https://wiki.apache.org/cassandra/NodeTool|website=Cassandra Wiki|access-date=5 January 2016|archive-url=https://web.archive.org/web/20160113122938/http://wiki.apache.org/cassandra/NodeTool|archive-date=13 January 2016|url-status=dead}}</ref> Nodetool also offers a number of commands to return Cassandra metrics pertaining to disk usage, latency, compaction, garbage collection, and more.<ref>{{cite web|title=How to monitor Cassandra performance metrics|date=3 December 2015|url=https://www.datadoghq.com/blog/how-to-monitor-cassandra-performance-metrics/|publisher=Datadog|access-date=5 January 2016}}</ref>
Since the release of Cassandra 2.0.2 in 2013, measures of several metrics are produced via the Dropwizard metrics framework,<ref>{{cite web|title=Metrics|url=https://wiki.apache.org/cassandra/Metrics|website=Cassandra Wiki|access-date=5 January 2016|archive-date=12 November 2015|archive-url=https://web.archive.org/web/20151112112756/http://wiki.apache.org/cassandra/Metrics|url-status=dead}}</ref> and may be queried via JMX using tools such as [[JConsole]] or passed to external monitoring systems via Dropwizard-compatible reporter plugins.<ref>{{cite web|title=Monitoring|url=http://cassandra.apache.org/doc/latest/operating/metrics.html|website=Cassandra Documentation|access-date=1 February 2018}}</ref>
== Releases ==
Releases after graduation include:
{| class="wikitable"
|-
! Version
! Original release date
! Latest version
! Release date
! Status<ref>
{{cite web |title=Cassandra Server Releases |url=http://cassandra.apache.org/download/ |access-date=15 December 2015 |work=cassandra.apache.org}}
</ref>
|-
| {{Version|o|0.6}}
| 2010-04-12
| 0.6.13
| 2011-04-18
| No longer maintained
|-
| {{Version|o|0.7}}
| 2011-01-10
| 0.7.10
| 2011-10-31
| No longer maintained
|-
| {{Version|o|0.8}}
| 2011-06-03
| 0.8.10
| 2012-02-13
| No longer maintained
|-
| {{Version|o|1.0}}
| 2011-10-18
| 1.0.12
| 2012-10-04
| No longer maintained
|-
| {{Version|o|1.1}}
| 2012-04-24
| 1.1.12
| 2013-05-27
| No longer maintained
|-
| {{Version|o|1.2}}
| 2013-01-02
| 1.2.19
| 2014-09-18
| No longer maintained
|-
| {{Version|o|2.0}}
| 2013-09-03
| 2.0.17
| 2015-09-21
| No longer maintained
|-
| {{Version|o|2.1}}
| 2014-09-16
| 2.1.22
| 2020-08-31
| No longer maintained
|-
| {{Version|o|2.2}}
| 2015-07-20
| 2.2.19
| 2020-11-04
| No longer maintained
|-
| {{Version|o|3.0}}
| 2015-11-09
| 3.0.29
| 2023-05-15
| No longer maintained
|-
| {{Version|o|3.11}}
| 2017-06-23
| 3.11.15
| 2023-05-05
| No longer maintained
|-
| {{Version|co|4.0}}
| 2021-07-26
| 4.0.18
| 2025-05-28
| Maintained until 5.1.0 release
|-
| {{Version|co|4.1}}
| 2022-06-17
| 4.1.9
| 2025-05-19
| Maintained until 5.2.0 release
|-
| {{Version|c|5.0}}
| 2024-09-05
| 5.0.5
| 2025-08-05
| Latest release. Maintained until 5.3.0 release
|-
| colspan="5" | <small>{{Version|l|show=111110}}</small>
|}
<!-- o=Old-Not-Supported; co=Old-Still-Supported; c=Latest-Stable; cp=Preview; p=Planned-Future -->
== See also ==
{{Portal|Free and open-source software}}
* [[Bigtable]] – Original distributed database by Google
* [[Distributed database]]
* [[Distributed hash table]] (DHT)
* [[Dynamo (storage system)]] – Cassandra borrows many elements from Dynamo
== References ==
{{Reflist|30em}}
==Bibliography==
{{refbegin}}
* {{cite book
| first1 =
| last1 =
|
| last2 = Hewitt
| date = January 23, 2022
| title = Cassandra: The Definitive Guide
| publisher = [[O'Reilly Media]]
| edition =
| page =
| isbn = 978-1-
}}
* {{cite book
| first1 = Edward
| last1 = Capriolo
Line 160 ⟶ 314:
| edition = 1st
| page = 324
| isbn = 978-1-84951-512-
| url = http://www.packtpub.com/cassandra-apache-high-performance-cookbook/book
}}
* {{cite book
| first1 = Eben
| last1 = Hewitt
| date = December 15, 2010
| title = Cassandra: The Definitive Guide
| publisher = [[O'Reilly Media]]
| edition = 1st
| page = 300
| isbn = 978-1-4493-9041-9
| url = http://shop.oreilly.com/product/0636920010852.do
}}
{{refend}}
==External links==
{{Commons category}}
{{Wikiversity|Big Data/Cassandra}}
* {{cite web |title=Cassandra - A structured storage system on a P2P Network |url=https://www.facebook.com/note.php?note_id=24413138919&id=9445547199&index=9 |first=Avinash |last=Lakshman
|date=2008-08-25 |access-date=2014-06-17 |publisher=Engineering @ Facebook's Notes}}
* {{cite web |url=https://cassandra.apache.org/ |title=The Apache Cassandra Project | * {{cite web |url=https://wiki.apache.org/cassandra/ |title=Project Wiki |
* {{cite web |url=http://www.infoq.com/presentations/Adopting-Apache-Cassandra |title=Adopting Apache Cassandra |first=Eben |last=Hewitt |date=2010-12-01 |
* {{cite web |first1=Avinash |last1=Lakshman |first2=Prashant |last2=Malik |url=https://www.cs.cornell.edu/projects/ladis2009/papers/lakshman-ladis2009.pdf |title=Cassandra - A Decentralized Structured Storage System |website=cs.cornell.edu |date=2009-08-15 |
* {{cite web |url=http://www.slideshare.net/jbellis/what-every-developer-should-know-about-database-scalability |title=What Every Developer Should Know About Database Scalability |first=Jonathan |last=Ellis |date=2009-07-29 |
* {{cite web |url=https://code.google.com/p/cassandra-rpm/ |title=Cassandra-RPM - Red Hat Package Manager (RPM) build for the Apache Cassandra project |website=code.google.com |
* {{cite web |url=http://de.slideshare.net/grro/cassandra-by-example-the-path-of-read-and-write-requests |title=Cassandra by example - the path of read and write requests |first=Gregor |last=Roth |date=2012-10-14|
* {{cite web |url=http://
* {{cite web|url=http://www.networkworld.com/news/tech/2012/102212-nosql-263595.html |title=A vendor-independent comparison of NoSQL databases: Cassandra, HBase, MongoDB, Riak |first=Sergey |last=Bushik |date=2012-10-22 |work=[[Network World|NetworkWorld]] |publisher=[[International Data Group|IDG]] |___location=Framingham, MA, USA and Staines, Middlesex, UK |access-date=2014-06-17 |url-status=dead |archive-url=https://web.archive.org/web/20140528110238/http://www.networkworld.com/news/tech/2012/102212-nosql-263595.html |archive-date=2014-05-28 }}
* {{cite web|url=https://db-engines.com/en/system/Apache+Cassandra|title=Apache Cassandra System Properties|work=DB-Engines|access-date=2025-05-28}}
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