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DBMS > Drizzle vs. Kyligence Enterprise vs. Milvus vs. Stardog

System Properties Comparison Drizzle vs. Kyligence Enterprise vs. Milvus vs. Stardog

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonMilvus  Xexclude from comparisonStardog  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A distributed analytics engine for big data, built on top of Apache KylinA DBMS designed for efficient storage of vector data and vector similarity searchesEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSRelational DBMSVector DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitekyligence.io/­kyligence-enterprisemilvus.iowww.stardog.com
Technical documentationmilvus.io/­docs/­overview.mddocs.stardog.com
DeveloperDrizzle project, originally started by Brian AkerKyligence, Inc.Stardog-Union
Initial release2008201620192010
Current release7.2.4, September 20122.3.4, January 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache Version 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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++JavaC++, GoJava
Server operating systemsFreeBSD
Linux
OS X
LinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Data schemeyesyesschema-free and OWL/RDFS-schema support
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 infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infowith proprietary extensionsANSI SQL for queries (using Apache Calcite)noYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C++
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnonouser defined functions and aggregates, HTTP Server extensions in Java
Triggersno infohooks for callbacks inside the server can be used.noyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnoyes inforelationships in graphs
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.noyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPRole based access control and fine grained access rightsAccess rights for users and roles
More information provided by the system vendor
DrizzleKyligence EnterpriseMilvusStardog
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
DrizzleKyligence EnterpriseMilvusStardog
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20 February 2020, Datanami

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10 August 2021, VentureBeat

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22 January 2021, Datanami

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20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

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