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DBMS > Citus vs. IBM Db2 Event Store vs. Machbase Neo vs. Spark SQL vs. Sphinx

System Properties Comparison Citus vs. IBM Db2 Event Store vs. Machbase Neo vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDistributed Event Store optimized for Internet of Things use casesTimeSeries DBMS for AIoT and BigDataSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Time Series DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.citusdata.comwww.ibm.com/­products/­db2-event-storemachbase.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.citusdata.comwww.ibm.com/­docs/­en/­db2-event-storemachbase.com/­dbmsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperIBMMachbaseApache Software FoundationSphinx Technologies Inc.
Initial release20102017201320142001
Current release8.1, December 20182.0V8.0, August 20233.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercial infofree developer edition availablecommercial infofree test version availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC and C++CScalaC++
Server operating systemsLinuxLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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 functionalitynonono
Secondary indexesyesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes infothrough the embedded Spark runtimeSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yesnonono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsActive-active shard replicationselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononono
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storagenoyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infovolatile and lookup tableno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardsimple password-based access controlnono

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More resources
CitusIBM Db2 Event StoreMachbase Neo infoFormer name was InfinifluxSpark SQLSphinx
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