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DBMS > Kinetica vs. Microsoft Azure Table Storage vs. RavenDB vs. Weaviate

System Properties Comparison Kinetica vs. Microsoft Azure Table Storage vs. RavenDB vs. Weaviate

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRavenDB  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSWide column storeDocument storeVector DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.92
Rank#101  Overall
#18  Document stores
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablesravendb.netgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.kinetica.comravendb.net/­docsweaviate.io/­developers/­weaviate
DeveloperKineticaMicrosoftHibernating RhinosWeaviate B.V.
Initial release2012201220102019
Current release7.1, August 20215.4, July 20221.19, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C#Go
Server operating systemsLinuxhostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesnoyes 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.nonono
Secondary indexesyesnoyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query language (RQL)GraphQL is used as query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresuser defined functionsnoyesno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding
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.Multi-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID, Cluster-wide transaction availableno
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.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesAuthorization levels configured per client per databaseAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
KineticaMicrosoft Azure Table StorageRavenDBWeaviate
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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More resources
KineticaMicrosoft Azure Table StorageRavenDBWeaviate
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