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DBMS > Kinetica vs. Oracle Berkeley DB vs. RDF4J vs. Spark SQL vs. TerarkDB

System Properties Comparison Kinetica vs. Oracle Berkeley DB vs. RDF4J vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsWidely used in-process key-value storeRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
RDF storeRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitewww.kinetica.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlrdf4j.orgspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationdocs.kinetica.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperKineticaOracle infooriginally developed by Sleepycat, which was acquired by OracleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software FoundationByteDance, originally Terark
Initial release20121994200420142016
Current release7.1, August 202118.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C, Java, C++ (depending on the Berkeley DB edition)JavaScalaC++
Server operating systemsLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes infoRDF Schemasyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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.noyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is availablenoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
C++ API
Java API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
PHP
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresuser defined functionsnoyesnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoonly for the SQL APIyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoIsolation support depends on the API usednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelnononono

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More resources
KineticaOracle Berkeley DBRDF4J infoformerly known as SesameSpark SQLTerarkDB
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