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DBMS > Kinetica vs. LeanXcale vs. Pinecone vs. Splice Machine

System Properties Comparison Kinetica vs. LeanXcale vs. Pinecone vs. Splice Machine

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonLeanXcale  Xexclude from comparisonPinecone  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA managed, cloud-native vector databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value store
Relational DBMS
Vector DBMSRelational 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
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.kinetica.comwww.leanxcale.comwww.pinecone.iosplicemachine.com
Technical documentationdocs.kinetica.comdocs.pinecone.io/­docs/­overviewsplicemachine.com/­how-it-works
DeveloperKineticaLeanXcalePinecone Systems, IncSplice Machine
Initial release2012201520192014
Current release7.1, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++Java
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesString, Number, Booleanyes
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 indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough Apache Derbynoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
Java
Scala
PythonC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoJava
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, 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 integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yes infoGPU vRAM or System RAMyesnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
KineticaLeanXcalePineconeSplice Machine
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