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DBMS > GridGain vs. Kyligence Enterprise vs. Milvus vs. TimescaleDB

System Properties Comparison GridGain vs. Kyligence Enterprise vs. Milvus vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonMilvus  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA distributed analytics engine for big data, built on top of Apache KylinA DBMS designed for efficient storage of vector data and vector similarity searchesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Relational DBMS
Relational DBMSVector DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score0.39
Rank#276  Overall
#125  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websitewww.gridgain.comkyligence.io/­kyligence-enterprisemilvus.iowww.timescale.com
Technical documentationwww.gridgain.com/­docs/­index.htmlmilvus.io/­docs/­overview.mddocs.timescale.com
DeveloperGridGain Systems, Inc.Kyligence, Inc.Timescale
Initial release2007201620192017
Current releaseGridGain 8.5.12.3.4, January 20242.13.0, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 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 languageJava, C++, .NetJavaC++, GoC
Server operating systemsLinux
OS X
Solaris
Windows
LinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringnumerics, 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.yesnonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLANSI SQL for queries (using Apache Calcite)noyes infofull PostgreSQL SQL syntax
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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.yesnoyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsRole based access control and fine grained access rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
GridGainKyligence EnterpriseMilvusTimescaleDB
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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GridGainKyligence EnterpriseMilvusTimescaleDB
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