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DBMS > Kinetica vs. Microsoft Access vs. RethinkDB vs. Splice Machine

System Properties Comparison Kinetica vs. Microsoft Access vs. RethinkDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRethinkDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)DBMS for the Web with a mechanism to push updated query results to applications in realtime.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.kinetica.comwww.microsoft.com/­en-us/­microsoft-365/­accessrethinkdb.comsplicemachine.com
Technical documentationdocs.kinetica.comdeveloper.microsoft.com/­en-us/­accessrethinkdb.com/­docssplicemachine.com/­how-it-works
DeveloperKineticaMicrosoftThe Linux Foundation infosince July 2017Splice Machine
Initial release2012199220092014
Current release7.1, August 20211902 (16.0.11328.20222), March 20192.4.1, August 20203.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++C++Java
Server operating systemsLinuxWindows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infostring, binary, float, bool, date, geometryyes
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infobut not compliant to any SQL standardnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infosince Access 2010 using the ACE-engineyes infoJava
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosince Access 2010 using the ACE-engineClient-side triggers through changefeedsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding inforange basedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infobut no files for transaction loggingAtomic single-document operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelno infoa simple user-level security was built in till version Access 2003yes infousers and table-level permissionsAccess rights for users, groups and roles according to SQL-standard

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More resources
KineticaMicrosoft AccessRethinkDBSplice Machine
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