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DBMS > GeoSpock vs. Splice Machine vs. Tkrzw vs. Yaacomo

System Properties Comparison GeoSpock vs. Splice Machine vs. Tkrzw vs. Yaacomo

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYaacomo  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionSpatial and temporal data processing engine for extreme data scaleOpen-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 CabinetOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegeospock.comsplicemachine.comdbmx.net/­tkrzwyaacomo.com
Technical documentationsplicemachine.com/­how-it-works
DeveloperGeoSpockSplice MachineMikio HirabayashiQ2WEB GmbH
Initial release201420202009
Current release2.0, September 20193.1, March 20210.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptJavaC++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS
Android
Linux
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonono
Secondary indexestemporal, categoricalyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)yesnoyes
APIs and other access methodsJDBCJDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoJavano
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShared Nothhing Auto-Sharding, Columnar Partitioningnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.noyesyes infousing specific database classesyes
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
GeoSpockSplice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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