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DBMS > Citus vs. Sadas Engine vs. Spark SQL vs. Sphinx

System Properties Comparison Citus vs. Sadas Engine vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsSpark 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 DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#141  Overall
#69  Relational DBMS
Score0.00
Rank#352  Overall
#146  Relational DBMS
Score21.87
Rank#34  Overall
#20  Relational DBMS
Score7.64
Rank#55  Overall
#5  Search engines
Websitewww.citusdata.comwww.sadasengine.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.citusdata.comwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperSADAS s.r.l.Apache Software FoundationSphinx Technologies Inc.
Initial release2010200620142001
Current release8.1, December 20188.03.1.1, March 20213.4.1, July 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++ScalaC++
Server operating systemsLinuxAIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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 functionalitynono
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesSQL-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
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
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.nonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, 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 extensionsnonenonenone
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 integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardnono

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More resources
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Recent citations in the news

How to Use Citus to Shard Postgres, for Performance & Scale - Microsoft
16 September 2021, Channel 9

Microsoft buys Citus Data
24 January 2019, ZDNet

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13 November 2018, Business Wire

Microsoft Expands Azure PostgreSQL Moxy Through Citus Data Purchase
30 January 2019, Data Center Knowledge

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