DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DocumentDB vs. Kinetica vs. Microsoft Azure AI Search vs. OpenQM

System Properties Comparison Amazon DocumentDB vs. Kinetica vs. Microsoft Azure AI Search vs. OpenQM

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFully vectorized database across both GPUs and CPUsSearch-as-a-service for web and mobile app developmentQpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelDocument storeRelational DBMSSearch engineMultivalue DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websiteaws.amazon.com/­documentdbwww.kinetica.comazure.microsoft.com/­en-us/­services/­searchwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperKineticaMicrosoftRocket Software, originally Martin Phillips
Initial release2019201220151993
Current release7.1, August 2021V13.4-12
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemshostedLinuxhostedAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeschema-freeyesyesyes infowith some exceptions
Typing infopredefined data types such as float or dateyesyesyes
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.nononoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsnoyes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replicationyes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonoACID
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 RAMno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles on table levelyes infousing Azure authenticationAccess rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon DocumentDBKineticaMicrosoft Azure AI SearchOpenQM infoalso called QM
Recent citations in the news

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

Game Developer's Guide to Amazon DocumentDB (with MongoDB compatibility) Part Three: Operation Best Practices ...
25 January 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

Perform near real time analytics using Amazon Redshift on data stored in Amazon DocumentDB | Amazon Web Services
14 February 2024, AWS Blog

provided by Google News

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

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

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

Kinetica Delivers Real-Time Vector Similarity Search
20 March 2024, Datanami

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, azure.microsoft.com

Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard) | Azure updates
2 April 2024, azure.microsoft.com

Microsoft’s Azure AI Search updated with increased storage, vector index size
5 April 2024, InfoWorld

Microsoft is a Leader in the 2024 Gartner® Magic Quadrant™ for Cloud AI Developer Services
3 May 2024, azure.microsoft.com

Microsoft Azure AI adds storage power, large RAG app support
5 April 2024, VentureBeat

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here