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DBMS > GridGain vs. Kinetica vs. Microsoft Azure Data Explorer vs. Weaviate

System Properties Comparison GridGain vs. Kinetica vs. Microsoft Azure Data Explorer vs. Weaviate

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedVector 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.gridgain.comwww.kinetica.comazure.microsoft.com/­services/­data-explorergithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerweaviate.io/­developers/­weaviate
DeveloperGridGain Systems, Inc.KineticaMicrosoftWeaviate B.V.
Initial release2007201220192019
Current releaseGridGain 8.5.17.1, August 2021cloud service with continuous releases1.19, May 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC, C++Go
Server operating systemsLinux
OS X
Solaris
Windows
Linuxhosted
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes 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.yesnoyesno
Secondary indexesyesyesall fields are automatically indexedyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetGraphQL is used as query language
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)user defined functionsYes, possible languages: KQL, Python, Rno
Triggersyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 dataACIDnonono
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.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users and roles on table levelAzure Active Directory AuthenticationAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
GridGainKineticaMicrosoft Azure Data ExplorerWeaviate
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...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GridGainKineticaMicrosoft Azure Data ExplorerWeaviate
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Weaviate, an ANN Database with CRUD support
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