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DBMS > Datomic vs. Kyligence Enterprise vs. Milvus vs. Vitess

System Properties Comparison Datomic vs. Kyligence Enterprise vs. Milvus vs. Vitess

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonMilvus  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed analytics engine for big data, built on top of Apache KylinA DBMS designed for efficient storage of vector data and vector similarity searchesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSVector DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.datomic.comkyligence.io/­kyligence-enterprisemilvus.iovitess.io
Technical documentationdocs.datomic.commilvus.io/­docs/­overview.mdvitess.io/­docs
DeveloperCognitectKyligence, Inc.The Linux Foundation, PlanetScale
Initial release2012201620192013
Current release1.0.6735, June 20232.3.4, January 202415.0.2, December 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0, commercial licenses available
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, ClojureJavaC++, GoGo
Server operating systemsAll OS with a Java VMLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Docker
Linux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoANSI SQL for queries (using Apache Calcite)noyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesClojure
Java
C++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infoproprietary syntax
TriggersBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyesyes
User concepts infoAccess controlnoRole based access control and fine grained access rightsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatomicKyligence EnterpriseMilvusVitess
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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DatomicKyligence EnterpriseMilvusVitess
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