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DBMS > ClickHouse vs. Kinetica vs. Solr

System Properties Comparison ClickHouse vs. Kinetica vs. Solr

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA 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.Fully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSSearch engine
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.31
Rank#37  Overall
#23  Relational DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score43.91
Rank#24  Overall
#3  Search engines
Websiteclickhouse.comwww.kinetica.comsolr.apache.org
Technical documentationclickhouse.com/­docsdocs.kinetica.comsolr.apache.org/­resources.html
DeveloperClickhouse Inc.KineticaApache Software Foundation
Initial release201620122006
Current releasev23.12.1.1368-stable, December 20237.1, August 20219.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2
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.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
  • ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Implementation languageC++C, C++Java
Server operating systemsFreeBSD
Linux
macOS
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like DML and DDL statementsSolr Parallel SQL Interface
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC# 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
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesuser defined functionsJava plugins
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeskey based and customShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic locking
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.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess 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.Access rights for users and roles on table levelyes

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Related products and services
3rd partiesAiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
» more

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
ClickHouseKineticaSolr
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