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DBMS > EXASOL vs. Kinetica vs. Microsoft Azure Table Storage vs. Milvus vs. RDF4J

System Properties Comparison EXASOL vs. Kinetica vs. Microsoft Azure Table Storage vs. Milvus vs. RDF4J

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonMilvus  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Fully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsA DBMS designed for efficient storage of vector data and vector similarity searchesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSRelational DBMSWide column storeVector DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.exasol.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablesmilvus.iordf4j.org
Technical documentationwww.exasol.com/­resourcesdocs.kinetica.commilvus.io/­docs/­overview.mdrdf4j.org/­documentation
DeveloperExasolKineticaMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20002012201220192004
Current release7.1, August 20212.3.4, January 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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, C++C++, GoJava
Server operating systemsLinuxhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Unix
Windows
Data schemeyesyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyesVector, 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.nononono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnonono
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIRESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesJava
Lua
Python
R
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnonoyes
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesRole based access control and fine grained access rightsno
More information provided by the system vendor
EXASOLKineticaMicrosoft Azure Table StorageMilvusRDF4J infoformerly known as Sesame
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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EXASOLKineticaMicrosoft Azure Table StorageMilvusRDF4J infoformerly known as Sesame
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