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DBMS > AnzoGraph DB vs. HEAVY.AI vs. Milvus vs. PouchDB

System Properties Comparison AnzoGraph DB vs. HEAVY.AI vs. Milvus vs. PouchDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMilvus  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA DBMS designed for efficient storage of vector data and vector similarity searchesJavaScript DBMS with an API inspired by CouchDB
Primary database modelGraph DBMS
RDF store
Relational DBMSVector DBMSDocument store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score3.01
Rank#89  Overall
#4  Vector DBMS
Score2.18
Rank#114  Overall
#21  Document stores
Websitecambridgesemantics.com/­anzographgithub.com/­heavyai/­heavydb
www.heavy.ai
milvus.iopouchdb.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.heavy.aimilvus.io/­docs/­overview.mdpouchdb.com/­guides
DeveloperCambridge SemanticsHEAVY.AI, Inc.Apache Software Foundation
Initial release2018201620192012
Current release2.3, January 20215.10, January 20222.4.4, May 20247.1.1, June 2019
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2.0Open Source
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++ and CUDAC++, GoJavaScript
Server operating systemsLinuxLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-free
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringno
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.nononono
Secondary indexesnononoyes infovia views
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yesnono
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
Thrift
Vega
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesC++
Java
Python
All languages supporting JDBC/ODBC/Thrift
Python
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoView functions in JavaScript
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoRound robinShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardRole based access control and fine grained access rightsno
More information provided by the system vendor
AnzoGraph DBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MilvusPouchDB
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 DBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MilvusPouchDB
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AnzoGraph: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics
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8 February 2019, Towards Data Science

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
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