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DBMS > Ignite vs. RDFox vs. Spark SQL vs. Splice Machine vs. Tkrzw

System Properties Comparison Ignite vs. RDFox vs. Spark SQL vs. Splice Machine vs. Tkrzw

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.High performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Relational DBMS
Graph DBMS
RDF store
Relational DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteignite.apache.orgwww.oxfordsemantic.techspark.apache.org/­sqlsplicemachine.comdbmx.net/­tkrzw
Technical documentationapacheignite.readme.io/­docsdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationOxford Semantic TechnologiesApache Software FoundationSplice MachineMikio Hirabayashi
Initial release20152017201420142020
Current releaseApache Ignite 2.66.0, Septermber 20223.5.0 ( 2.13), September 20233.1, March 20210.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
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 languageC++, Java, .NetC++ScalaJavaC++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Data schemeyesyes infoRDF schemasyesyesschema-free
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statementsyesno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
Java
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noyes infoJavano
Triggersyes (cache interceptors and events)noyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)replication via a shared file systemnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)Yes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes infousing specific database classes
User concepts infoAccess controlSecurity Hooks for custom implementationsRoles, resources, and access typesnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
IgniteRDFoxSpark SQLSplice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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