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

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

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsWidely used in-process key-value storeSpark 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 MongoDBA secure RDBMS, designed for easy portability from Oracle
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value storeRelational DBMS
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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Score1.59
Rank#148  Overall
#68  Relational DBMS
Websitewww.kinetica.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdbus.tmaxsoft.com/­products/­tibero
Technical documentationdocs.kinetica.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKctechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperKineticaOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally TerarkTmaxSoft
Initial release20121994201420162003
Current release7.1, August 202118.1.40, May 20203.5.0 ( 2.13), September 20236, April 2015
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoApache 2.0commercial inforestricted open source version availablecommercial
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, C++C, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and Assembler
Server operating systemsLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoyes
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 editionnonoyes
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
C++ API
Java API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
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
Python
R
Scala
C++
Java
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsnononoPersistent Stored Procedure (PSM)
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenonehorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnonenoneMulti-source replication
Source-replica replication
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 configurationImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yes infoGPU vRAM or System RAMyesnoyesno infoplanned for next version
User concepts infoAccess controlAccess rights for users and roles on table levelnononofine grained access rights according to SQL-standard (SQL 92, SQL 99)

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More resources
KineticaOracle Berkeley DBSpark SQLTerarkDBTibero
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