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DBMS > Kinetica vs. Pinecone vs. Transwarp StellarDB

System Properties Comparison Kinetica vs. Pinecone vs. Transwarp StellarDB

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPinecone  Xexclude from comparisonTranswarp StellarDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA managed, cloud-native vector databaseA distributed graph DBMS built for enterprise-level graph applications
Primary database modelRelational DBMSVector DBMSGraph DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score3.02
Rank#87  Overall
#3  Vector DBMS
Score0.00
Rank#385  Overall
#40  Graph DBMS
Websitewww.kinetica.comwww.pinecone.iowww.transwarp.cn/­en/­product/­stellardb
Technical documentationdocs.kinetica.comdocs.pinecone.io/­docs/­overview
DeveloperKineticaPinecone Systems, IncTranswarp
Initial release20122019
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemsLinuxhosted
Data schemeyes
Typing infopredefined data types such as float or dateyesString, Number, Boolean
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 indexesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIOpenCypher
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Python
Server-side scripts infoStored proceduresuser defined functions
Triggersyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelyes

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More resources
KineticaPineconeTranswarp StellarDB
DB-Engines blog posts

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