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DBMS > Apache Cassandra vs. Apache Druid vs. ClickHouse

System Properties Comparison Apache Cassandra vs. Apache Druid vs. ClickHouse

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Editorial information provided by DB-Engines
NameApache Cassandra  Xexclude from comparisonApache Druid  Xexclude from comparisonClickHouse  Xexclude from comparison
DescriptionWide-column store based on ideas of BigTable and DynamoDB infoOptimized for write accessOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.
Primary database modelWide column storeRelational DBMS
Time Series DBMS
Relational DBMS
Secondary database modelsVector DBMS infostarting with release V5Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score102.58
Rank#11  Overall
#1  Wide column stores
Score2.86
Rank#90  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score18.71
Rank#30  Overall
#18  Relational DBMS
Websitecassandra.apache.orgdruid.apache.orgclickhouse.com
Technical documentationcassandra.apache.org/­doc/­latestdruid.apache.org/­docs/­latest/­designclickhouse.com/­docs
DeveloperApache Software Foundation infoApache top level project, originally developped by FacebookApache Software Foundation and contributorsClickhouse Inc.
Initial release200820122016
Current release5.0-rc1, July 202430.0.0, June 2024v24.6.2.17-stable, July 2024
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache license v2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsBSD
Linux
OS X
Windows
Linux
OS X
Unix
FreeBSD
Linux
macOS
Data schemeschema-freeyes infoschema-less columns are supportedyes
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesrestricted infoonly equality queries, not always the best performing solutionyesyes
SQL infoSupport of SQLSQL-like SELECT, DML and DDL statements (CQL)SQL for queryingClose to ANSI SQL (SQL/JSON + extensions)
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language, an SQL-like language)
Thrift
JDBC
RESTful HTTP/JSON API
gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesC#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript infoNode.js
Perl
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
Server-side scripts infoStored proceduresnonoyes
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"Sharding infomanual/auto, time-basedkey based and custom
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoRepresentation of geographical distribution of servers is possibleyes, via HDFS, S3 or other storage enginesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users can be defined per objectRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.
More information provided by the system vendor
Apache CassandraApache DruidClickHouse
Specific characteristicsApache Cassandra is the leading NoSQL, distributed database management system, well...
» more
Competitive advantagesNo single point of failure ensures 100% availability . Operational simplicity for...
» more
Typical application scenariosInternet of Things (IOT), fraud detection applications, recommendation engines, product...
» more
Key customersApple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more
Market metricsApache Cassandra is used by 40% of the Fortune 100.
» more
Licensing and pricing modelsApache license  Pricing for commercial distributions provided by DataStax and available...
» more
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More resources
Apache CassandraApache DruidClickHouse
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