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DBMS > Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. RethinkDB

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. RethinkDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRethinkDB  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.27
Rank#108  Overall
#7  Wide column stores
Score2.66
Rank#97  Overall
#48  Relational DBMS
Score3.63
Rank#81  Overall
#15  Document stores
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorerrethinkdb.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerrethinkdb.com/­docs
DeveloperGoogleMicrosoftThe Linux Foundation infosince July 2017
Initial release201520192009
Current release2.4.0, December 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedLinux
OS X
Windows
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyes 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 indexesnoyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.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
TriggersnoTable-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 nodesShardingSharding infoImplicit feature of the cloud serviceSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes 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 (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row 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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationyes infousers and table-level permissions

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