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DBMS > ClickHouse vs. Kinetica vs. SvectorDB

System Properties Comparison ClickHouse vs. Kinetica vs. SvectorDB

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonKinetica  Xexclude from comparisonSvectorDB  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 CPUsServerless cloud-native vector database infoServerless cloud-native vector database
Primary database modelRelational DBMSRelational DBMSVector DBMS
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.44
Rank#31  Overall
#19  Relational DBMS
Score0.45
Rank#254  Overall
#118  Relational DBMS
Score0.00
Rank#392  Overall
#19  Vector DBMS
Websiteclickhouse.comwww.kinetica.comsvectordb.com
Technical documentationclickhouse.com/­docsdocs.kinetica.comwww.svectordb.com/­docs
DeveloperClickhouse Inc.KineticaSvectorDB
Initial release201620122023
Current releasev24.6.2.17-stable, July 20247.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
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.
  • 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++
Server operating systemsFreeBSD
Linux
macOS
Linuxserver-less
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyesstring, double, vector
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 indexesyesyes
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like DML and DDL statements
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
JDBC
ODBC
RESTful HTTP API
OpenAPI 3.0, RESTful HTTP API, Python SDK, JavaScript / TypeScript SDK
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
Server-side scripts infoStored proceduresyesuser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeskey based and customSharding
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
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 RAM
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 level

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Related products and services
3rd partiesDoubleCloud: 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
ClickHouseKineticaSvectorDB
Recent citations in the news

A Beginner’s Guide to ClickHouse Database
13 September 2024, KDnuggets

Real-time database startup ClickHouse acquires PeerDB to expand its Postgres support
30 July 2024, TechCrunch

Database startup ClickHouse Announces PeerDB Acquistion
31 July 2024, Tech Times

Azur Games migrates all game analytics data to ClickHouse Cloud on AWS
16 July 2024, AWS Blog

ClickHouse Acquires PeerDB to Boost Real-time Analytics with Postgres CDC Integration
30 July 2024, Business Wire

provided by Google News

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica: AI is a ‘killer app’ for data analytics
2 May 2023, Blocks and Files

How GPUs Are Helping Paris’ Public Hospital System Combat the Spread of COVID-19
15 October 2020, NVIDIA Blog

Kinetica Launches Industry-First Active Analytics Platform
13 March 2019, Business Wire

Kinetica Now Available as a Service in AWS Marketplace
29 September 2022, PR Newswire

provided by Google News



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