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DBMS > Apache Pinot vs. Splice Machine vs. Tkrzw

System Properties Comparison Apache Pinot vs. Splice Machine vs. Tkrzw

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyOpen-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 modelRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#274  Overall
#128  Relational DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websitepinot.apache.orgsplicemachine.comdbmx.net/­tkrzw
Technical documentationdocs.pinot.apache.orgsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsSplice MachineMikio Hirabayashi
Initial release201520142020
Current release1.0.0, September 20233.1, March 20210.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java JDK11 or higherLinux
OS X
Solaris
Windows
Linux
macOS
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.no
Secondary indexesyes
SQL infoSupport of SQLSQL-like query languageyesno
APIs and other access methodsJDBCJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavano
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache PinotSplice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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