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DBMS > Kinetica vs. Kyligence Enterprise vs. Milvus vs. Sphinx vs. TimescaleDB

System Properties Comparison Kinetica vs. Kyligence Enterprise vs. Milvus vs. Sphinx vs. TimescaleDB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonMilvus  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA distributed analytics engine for big data, built on top of Apache KylinA DBMS designed for efficient storage of vector data and vector similarity searchesOpen source search engine for searching in data from different sources, e.g. relational databasesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSVector DBMSSearch engineTime Series 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
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.kinetica.comkyligence.io/­kyligence-enterprisemilvus.iosphinxsearch.comwww.timescale.com
Technical documentationdocs.kinetica.commilvus.io/­docs/­overview.mdsphinxsearch.com/­docsdocs.timescale.com
DeveloperKineticaKyligence, Inc.Sphinx Technologies Inc.Timescale
Initial release20122016201920012017
Current release7.1, August 20212.3.4, January 20243.5.1, February 20232.13.0, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
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++JavaC++, GoC++C
Server operating systemsLinuxLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)noSQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIProprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyesno
User concepts infoAccess controlAccess rights for users and roles on table levelRole based access control and fine grained access rightsnofine grained access rights according to SQL-standard
More information provided by the system vendor
KineticaKyligence EnterpriseMilvusSphinxTimescaleDB
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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More resources
KineticaKyligence EnterpriseMilvusSphinxTimescaleDB
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