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DBMS > Kinetica vs. ObjectBox vs. Pinecone vs. Splice Machine vs. Yanza

System Properties Comparison Kinetica vs. ObjectBox vs. Pinecone vs. Splice Machine vs. Yanza

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonObjectBox  Xexclude from comparisonPinecone  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFully vectorized database across both GPUs and CPUsExtremely fast embedded database for small devices, IoT and MobileA managed, cloud-native vector databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS for IoT Applications
Primary database modelRelational DBMSObject oriented DBMSVector DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.kinetica.comobjectbox.iowww.pinecone.iosplicemachine.comyanza.com
Technical documentationdocs.kinetica.comdocs.objectbox.iodocs.pinecone.io/­docs/­overviewsplicemachine.com/­how-it-works
DeveloperKineticaObjectBox LimitedPinecone Systems, IncSplice MachineYanza
Initial release20122017201920142015
Current release7.1, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0commercialOpen Source infoAGPL 3.0, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C and C++Java
Server operating systemsLinuxAndroid
iOS
Linux
macOS
Windows
hostedLinux
OS X
Solaris
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesString, Number, Booleanyesno
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary native APIRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
PythonC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsnoyes infoJavano
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationonline/offline synchronization between client and serverMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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 RAMnonoyes
User concepts infoAccess controlAccess rights for users and roles on table levelyesAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
KineticaObjectBoxPineconeSplice MachineYanza
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