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DBMS > Citus vs. Heroic vs. Spark SQL

System Properties Comparison Citus vs. Heroic vs. Spark SQL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHeroic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.27
Rank#151  Overall
#75  Relational DBMS
Score0.46
Rank#231  Overall
#14  Time Series DBMS
Score19.47
Rank#33  Overall
#20  Relational DBMS
Websitewww.citusdata.comspotify.github.io/­heroic/­#!/­indexspark.apache.org/­sql
Technical documentationdocs.citusdata.comspotify.github.io/­heroic/­#!/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSpotifyApache Software Foundation
Initial release201020142014
Current release8.1, December 20183.0.1, October 2020
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaScala
Server operating systemsLinuxLinux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyes infovia Elasticsearchno
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
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 nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate 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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardno

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More resources
CitusHeroicSpark SQL
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