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DBMS > Kinetica vs. Milvus vs. TimescaleDB vs. Trafodion

System Properties Comparison Kinetica vs. Milvus vs. TimescaleDB vs. Trafodion

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMilvus  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFully vectorized database across both GPUs and CPUsA DBMS designed for efficient storage of vector data and vector similarity searchesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSVector DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.kinetica.commilvus.iowww.timescale.comtrafodion.apache.org
Technical documentationdocs.kinetica.commilvus.io/­docs/­overview.mddocs.timescale.comtrafodion.apache.org/­documentation.html
DeveloperKineticaTimescaleApache Software Foundation, originally developed by HP
Initial release2012201920172014
Current release7.1, August 20212.3.4, January 20242.15.0, May 20242.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0
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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC, C++C++, GoCC++, Java
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functionsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellJava Stored Procedures
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with hot standby and reads on replicas infoyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 RAMyesnono
User concepts infoAccess controlAccess rights for users and roles on table levelRole based access control and fine grained access rightsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
KineticaMilvusTimescaleDBTrafodion
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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KineticaMilvusTimescaleDBTrafodion
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