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DBMS > chDB vs. Citus vs. Spark SQL vs. STSdb

System Properties Comparison chDB vs. Citus vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NamechDB  Xexclude from comparisonCitus  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAn embedded SQL OLAP Engine powered by ClickHouseScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsTime Series DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.07
Rank#376  Overall
#158  Relational DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitegithub.com/­chdb-io/­chdbwww.citusdata.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdoc.chdb.iodocs.citusdata.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationSTS Soft SC
Initial release2023201020142011
Current release8.1, December 20183.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availableOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScalaC#
Server operating systemsserver-lessLinuxLinux
OS X
Windows
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)
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.yes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesnono
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)yes infostandard, with numerous extensionsSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
.NET Client API
Supported programming languagesBun
C
C++
Go
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardnono

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More resources
chDBCitusSpark SQLSTSdb
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