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DBMS > ClickHouse vs. Databricks vs. GBase

System Properties Comparison ClickHouse vs. Databricks vs. GBase

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonDatabricks  Xexclude from comparisonGBase  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.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.44
Rank#31  Overall
#19  Relational DBMS
Score87.68
Rank#13  Overall
#2  Document stores
#9  Relational DBMS
Score1.17
Rank#169  Overall
#77  Relational DBMS
Websiteclickhouse.comwww.databricks.comwww.gbase.cn
Technical documentationclickhouse.com/­docsdocs.databricks.com
DeveloperClickhouse Inc.DatabricksGeneral Data Technology Co., Ltd.
Initial release201620132004
Current releasev24.6.2.17-stable, July 2024GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • 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.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Implementation languageC++C, Java, Python
Server operating systemsFreeBSD
Linux
macOS
hostedLinux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes
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.noyesyes
Secondary indexesyesyesyes
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)with Databricks SQLStandard with numerous extensions
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
JDBC
ODBC
RESTful HTTP API
ADO.NET
C API
JDBC
ODBC
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
Python
R
Scala
C#
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesuser defined functions
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodeskey based and customhorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.yesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.yesno
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.yes
More information provided by the system vendor
ClickHouseDatabricksGBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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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
ClickHouseDatabricksGBase
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A Beginner’s Guide to ClickHouse Database
13 September 2024, KDnuggets

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30 July 2024, TechCrunch

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30 October 2024, ibm.com

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13 November 2024, Reuters

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13 November 2024, Yahoo Finance

Databricks and the path to AI-driven data intelligence
4 December 2024, SiliconANGLE News

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