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DBMS > Citus vs. Fujitsu Enterprise Postgres vs. Heroic vs. Warp 10

System Properties Comparison Citus vs. Fujitsu Enterprise Postgres vs. Heroic vs. Warp 10

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHeroic  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.citusdata.comwww.postgresql.fastware.comgithub.com/­spotify/­heroicwww.warp10.io
Technical documentationdocs.citusdata.comwww.postgresql.fastware.com/­product-manualsspotify.github.io/­heroicwww.warp10.io/­content/­02_Getting_started
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySpotifySenX
Initial release201020142015
Current release8.1, December 2018Fujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache 2.0Open Source infoApache License 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 languageCCJavaJava
Server operating systemsLinuxLinux
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeschema-free
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.yes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyes infovia Elasticsearchno
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesnono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HQL (Heroic Query Language, a JSON-based language)
HTTP API
HTTP API
Jupyter
WebSocket
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsnoyes infoWarpScript
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
CitusFujitsu Enterprise PostgresHeroicWarp 10
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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CitusFujitsu Enterprise PostgresHeroicWarp 10
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