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DBMS > ClickHouse vs. Dolt vs. QuestDB vs. Spark SQL

System Properties Comparison ClickHouse vs. Dolt vs. QuestDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonDolt  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionColumn-oriented Relational DBMS powering YandexA MySQL compatible DBMS with Git-like versioning of data and schemaA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.32
Rank#46  Overall
#30  Relational DBMS
Score0.62
Rank#218  Overall
#106  Relational DBMS
Score1.19
Rank#161  Overall
#12  Time Series DBMS
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websiteclickhouse.techgithub.com/­dolthub/­dolt
www.dolthub.com
questdb.iospark.apache.org/­sql
Technical documentationclickhouse.tech/­docsdocs.dolthub.comquestdb.io/­docs/­introductionspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperClickhouse Inc.DoltHub IncQuestDB LimitedApache Software Foundation
Initial release2016201820142014
Current releasev22.3.3.44-lts, April 20223.2.0, October 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJavaScala
Server operating systemsFreeBSD
Linux
macOS
Linux
macOS
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLClose to ANSI SQLyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsHTTP REST
JDBC
ODBC
Proprietary protocol
CLI Client
HTTP REST
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
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
Scala info3rd party library
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infocurrently in alpha releasenono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Configurable consistency for N replicasnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infothrough memory mapped filesno
User concepts infoAccess controlAccess rights for users and rolesOnly one user is configurable, and must be specified in the config file at startupno
More information provided by the system vendor
ClickHouseDoltQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column based storage and time partitioned...
» more
Competitive advantagesReal-time data ingestion and istant SQL queries for time series High performance...
» more
Typical application scenariosApplication metrics Financial market data and algo trading DevOps monitoring Real-time...
» more
Licensing and pricing modelsApache 2.0.
» more
News

QuestDB 6.3 Release Highlights
9 May 2022

Time Series Data Analytics with QuestDB and Cube
26 April 2022

Demo of live crypto data streamed with QuestDB and Grafana
12 April 2022

Calling on our community members to help us support Ukraine
7 March 2022

QuestDB 6.2 January release, SQL JIT compiler
27 January 2022

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesSQLFlow: Provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across Databases, ETL, Business Intelligence, Cloud and Hadoop environments by parsing SQL Script and stored procedure.
» more

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

More resources
ClickHouseDoltQuestDBSpark SQL
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