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DBMS > AnzoGraph DB vs. Citus vs. Milvus

System Properties Comparison AnzoGraph DB vs. Citus vs. Milvus

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonCitus  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelGraph DBMS
RDF store
Relational DBMSVector DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score2.13
Rank#117  Overall
#56  Relational DBMS
Score3.01
Rank#89  Overall
#4  Vector DBMS
Websitecambridgesemantics.com/­anzographwww.citusdata.commilvus.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.citusdata.commilvus.io/­docs/­overview.md
DeveloperCambridge Semantics
Initial release201820102019
Current release2.3, January 20218.1, December 20182.4.4, May 2024
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
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 languageCC++, Go
Server operating systemsLinuxLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeSchema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesVector, Numeric and String
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.noyes infospecific XML type available, but no XML query functionalityno
Secondary indexesnoyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infostandard, with numerous extensionsno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesC++
Java
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityno infonot needed in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
AnzoGraph DBCitusMilvus
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
AnzoGraph DBCitusMilvus
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

AnzoGraph: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics
19 June 2020, Solutions Review

AWS Launches New Analytics Engine That Combines the Power Of Vector Search And Graph Data
1 December 2023, EnterpriseAI

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Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL performance and scale
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5 March 2024, TechCrunch

Microsoft acquires Citus Data, creators of a cloud-friendly version of the PostgreSQL database
24 January 2019, GeekWire

Microsoft acquires another open-source company, Citus Data
24 January 2019, CNBC

Citus Data Announces Citus Cloud Database Support for HIPAA and SOC 2 Type 2 Compliance
13 November 2018, businesswire.com

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How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

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IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
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