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DBMS > AnzoGraph DB vs. Apache IoTDB vs. HyperSQL vs. Milvus

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. HyperSQL vs. Milvus

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  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 virtualizationAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orghsqldb.orgmilvus.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhsqldb.org/­web/­hsqlDocsFrame.htmlmilvus.io/­docs/­overview.md
DeveloperCambridge SemanticsApache Software Foundation
Initial release2018201820012019
Current release2.3, January 20211.1.0, April 20232.7.2, June 20232.3.4, January 2024
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infobased on BSD licenseOpen Source infoApache Version 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 languageJavaJavaC++, Go
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeSchema-free and OWL/RDFS-schema supportyesyes
Typing infopredefined data types such as float or dateyesyesVector, 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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyesno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
HTTP API infoJDBC via HTTP
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC
Java
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesJava, SQLno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.yesyesyesyes
User concepts infoAccess controlAccess rights for users and rolesyesfine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
AnzoGraph DBApache IoTDBHyperSQL infoalso known as HSQLDBMilvus
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 DBApache IoTDBHyperSQL infoalso known as HSQLDBMilvus
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