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DBMS > Datastax Enterprise vs. GridDB vs. Microsoft Azure AI Search

System Properties Comparison Datastax Enterprise vs. GridDB vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Scalable in-memory time series database optimized for IoT and Big DataSearch-as-a-service for web and mobile app development
Primary database modelWide column storeTime Series DBMSSearch engine
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Key-value store
Relational DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.31
Rank#57  Overall
#4  Wide column stores
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Websitewww.datastax.com/­products/­datastax-enterprisegriddb.netazure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.datastax.comdocs.griddb.netlearn.microsoft.com/­en-us/­azure/­search
DeveloperDataStaxToshiba CorporationMicrosoft
Initial release201120132015
Current release6.8, April 20205.1, August 2022V1
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Linuxhosted
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnonono
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingSource-replica replicationyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per objectAccess rights for users can be defined per databaseyes infousing Azure authentication
More information provided by the system vendor
Datastax EnterpriseGridDBMicrosoft Azure AI Search
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
GitHub trending repository
» more
Licensing and pricing modelsAnnual subscription
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Datastax EnterpriseGridDBMicrosoft Azure AI Search
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