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DBMS > IRONdb vs. Kinetica vs. Microsoft Azure Data Explorer vs. RDF4J vs. Weaviate

System Properties Comparison IRONdb vs. Kinetica vs. Microsoft Azure Data Explorer vs. RDF4J vs. Weaviate

Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonWeaviate  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.An AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedRDF storeVector DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score1.52
Rank#153  Overall
#6  Vector DBMS
Websitewww.circonus.com/solutions/time-series-database/www.kinetica.comazure.microsoft.com/­services/­data-explorerrdf4j.orggithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentationweaviate.io/­developers/­weaviate
DeveloperCirconus LLC.KineticaMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Weaviate B.V.
Initial release20172012201920042019
Current releaseV0.10.20, January 20187.1, August 2021cloud service with continuous releases1.19, May 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infocommercial license available with Weaviate Enterprise
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.
Implementation languageC and C++C, C++JavaGo
Server operating systemsLinuxLinuxhostedLinux
OS X
Unix
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemasyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyes infotext, numeric, histogramsyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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.nonoyesno
Secondary indexesnoyesall fields are automatically indexedyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetnoGraphQL is used as query language
APIs and other access methodsHTTP APIJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
PHP
Python
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyes, in Luauser defined functionsYes, possible languages: KQL, Python, Ryesno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeShardingSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlnoAccess rights for users and roles on table levelAzure Active Directory AuthenticationnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
IRONdbKineticaMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameWeaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
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Key customersAll companies that have data. ​
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Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
IRONdbKineticaMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameWeaviate
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