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DBMS > BigObject vs. Kdb vs. Kinetica vs. Oracle Berkeley DB

System Properties Comparison BigObject vs. Kdb vs. Kinetica vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonKdb  Xexclude from comparisonKinetica  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesHigh performance Time Series DBMSFully vectorized database across both GPUs and CPUsWidely used in-process key-value store
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMS
Vector DBMS
Relational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitebigobject.iokx.comwww.kinetica.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.bigobject.iocode.kx.comdocs.kinetica.comdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperBigObject, Inc.Kx Systems, a division of First Derivatives plcKineticaOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20152000 infokdb was released 2000, kdb+ in 200320121994
Current release3.6, May 20187.1, August 202118.1.40, May 2020
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial infofree 32-bit versioncommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqC, C++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Solaris
Windows
LinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.noyesnoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyes infotable attribute 'grouped'yesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (q)SQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is available
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++
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
Server-side scripts infoStored proceduresLuauser defined functionsuser defined functionsno
Triggersnoyes infowith viewsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-replica replicationSource-replica replication
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 systemnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)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.yesyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlnorights management via user accountsAccess rights for users and roles on table levelno
More information provided by the system vendor
BigObjectKdbKineticaOracle Berkeley DB
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...
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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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BigObjectKdbKineticaOracle Berkeley DB
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