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DBMS > Citus vs. Hypertable vs. Ignite vs. Splice Machine

System Properties Comparison Citus vs. Hypertable vs. Ignite vs. Splice Machine

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHypertable  Xexclude from comparisonIgnite  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAn open source BigTable implementation based on distributed file systems such as HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSWide column storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.citusdata.comignite.apache.orgsplicemachine.com
Technical documentationdocs.citusdata.comapacheignite.readme.io/­docssplicemachine.com/­how-it-works
DeveloperHypertable Inc.Apache Software FoundationSplice Machine
Initial release2010200920152014
Current release8.1, December 20180.9.8.11, March 2016Apache Ignite 2.63.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0Open Source infoAGPL 3.0, 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 languageCC++C++, Java, .NetJava
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 functionalityyes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
C++ API
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
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.noyes (compute grid and cache interceptors can be used instead)yes infoJava
Triggersyesnoyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factor on file system levelyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)Yes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoSecurity Hooks for custom implementationsAccess rights for users, groups and roles according to SQL-standard

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CitusHypertableIgniteSplice Machine
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