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DBMS > Ehcache vs. Kdb vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB

System Properties Comparison Ehcache vs. Kdb vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonKdb  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsHigh performance Time Series DBMSWidely 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 MongoDB
Primary database modelKey-value storeTime Series DBMS
Vector DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.ehcache.orgkx.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationwww.ehcache.org/­documentationcode.kx.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperTerracotta Inc, owned by Software AGKx Systems, a division of First Derivatives plcOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally Terark
Initial release20092000 infokdb was released 2000, kdb+ in 2003199420142016
Current release3.10.0, March 20223.6, May 201818.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercial infofree 32-bit versionOpen Source infocommercial license availableOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaqC, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesno
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.noyesyes infoonly with the Berkeley DB XML editionnono
Secondary indexesnoyes infotable attribute 'grouped'yesnono
SQL infoSupport of SQLnoSQL-like query language (q)yes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsno
APIs and other access methodsJCacheHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
C++ API
Java API
Supported programming languagesJavaC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.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
Server-side scripts infoStored proceduresnouser defined functionsnonono
Triggersyes infoCache Event Listenersyes infowith viewsyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta Serverhorizontal partitioningnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerSource-replica replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesnoyes
User concepts infoAccess controlnorights management via user accountsnonono
More information provided by the system vendor
EhcacheKdbOracle Berkeley DBSpark SQLTerarkDB
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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EhcacheKdbOracle Berkeley DBSpark SQLTerarkDB
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