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DBMS > Kinetica vs. Qdrant vs. RDF4J vs. Stardog

System Properties Comparison Kinetica vs. Qdrant vs. RDF4J vs. Stardog

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonQdrant  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA high-performance vector database with neural network or semantic-based matchingRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSVector DBMSRDF storeGraph DBMS
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score1.53
Rank#145  Overall
#7  Vector DBMS
Score0.72
Rank#222  Overall
#9  RDF stores
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Websitewww.kinetica.comgithub.com/­qdrant/­qdrant
qdrant.tech
rdf4j.orgwww.stardog.com
Technical documentationdocs.kinetica.comqdrant.tech/­documentationrdf4j.org/­documentationdocs.stardog.com
DeveloperKineticaQdrantSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Stardog-Union
Initial release2012202120042010
Current release7.1, August 20217.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoEclipse Distribution License (EDL), v1.0.commercial 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.
Implementation languageC, C++RustJavaJava
Server operating systemsLinuxDocker
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Linux
macOS
Windows
Data schemeyesschema-freeyes infoRDF Schemasschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanyesyes
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 indexesyesyes infoKeywords, numberic ranges, geo, full-textyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
GraphQL 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++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Java
PHP
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyesuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationCollection-level replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency, tunable consistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelKey-based authenticationnoAccess rights for users and roles

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More resources
KineticaQdrantRDF4J infoformerly known as SesameStardog
Recent citations in the news

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica: AI is a ‘killer app’ for data analytics
2 May 2023, Blocks & Files

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29 July 2024, InfoWorld

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

provided by Google News



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