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DBMS > Datastax Enterprise vs. Microsoft Azure Data Explorer vs. RethinkDB

System Properties Comparison Datastax Enterprise vs. Microsoft Azure Data Explorer vs. RethinkDB

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRethinkDB  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.Fully managed big data interactive analytics platformDBMS for the Web with a mechanism to push updated query results to applications in realtime.
Primary database modelWide column storeRelational DBMSDocument store
Secondary database modelsDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.66
Rank#44  Overall
#4  Wide column stores
Score2.33
Rank#104  Overall
#50  Relational DBMS
Score3.76
Rank#77  Overall
#13  Document stores
Websitewww.datastax.com/­products/­datastax-enterpriseazure.microsoft.com/­services/­data-explorerrethinkdb.com
Technical documentationdocs.datastax.comdocs.microsoft.com/­en-us/­azure/­data-explorerrethinkdb.com/­docs
DeveloperDataStaxMicrosoftThe Linux Foundation infosince July 2017
Initial release201120192009
Current release6.7, December 20182.4.0, December 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
hostedLinux
OS X
Windows
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infostring, binary, float, bool, date, geometry
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.noyesno
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLKusto Query Language (KQL), SQL subsetno
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Server-side scripts infoStored proceduresnoYes. Languages: KQL, Python, R
TriggersyesTable-level update policy rules can be used to automatically run a query and ingest its results when data is ingested into another table.Client-side triggers through changefeeds
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"Sharding infoImplicit feature of the cloud serviceSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Master-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Immediate Consistency
Immediate 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 operationsnoAtomic single-document operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC based
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.yesnono
User concepts infoAccess controlAccess rights for users can be defined per objectAzure Active Directory Authenticationyes infousers and table-level permissions
More information provided by the system vendor
Datastax EnterpriseMicrosoft Azure Data ExplorerRethinkDB
Specific characteristics100% continuous availability, real-time, distributed, massive scale data management...
» more
Competitive advantagesSupporting the following application requirements: Contextual: complete data layer...
» more
Typical application scenariosApplications that must serve contextual information and be always-on, distributed,...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald’s, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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Datastax EnterpriseMicrosoft Azure Data ExplorerRethinkDB
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