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DBMS > ClickHouse vs. Google Search Appliance vs. Microsoft Azure Data Explorer

System Properties Comparison ClickHouse vs. Google Search Appliance vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonGoogle Search Appliance  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionColumn-oriented Relational DBMS powering YandexThe Google Search Appliance consists of hardware and software for indexing documents in local networks.Fully managed big data interactive analytics platform
Primary database modelRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.33
Rank#82  Overall
#41  Relational DBMS
Score2.77
Rank#94  Overall
#10  Search engines
Score2.00
Rank#113  Overall
#55  Relational DBMS
Websiteclickhouse.yandexenterprise.google.com/­search/­products/­gsa.htmlazure.microsoft.com/­services/­data-explorer
Technical documentationclickhouse.yandex/­docssupport.google.com/­gsadocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperYandex LLCGoogleMicrosoft
Initial release201620022019
Current releasev19.13.3.26, August 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial
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.
Server operating systemshosted
Data schemeyes
Typing infopredefined data types such as float or dateyes
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.noyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subset
APIs and other access methodsAdministrative API
Browser interface
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresYes. Languages: KQL, Python, R
TriggersTable-level update policy rules can be used to automatically run a query and ingest its results when data is ingested into another table.
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlUser authentication via various security protocolsAzure Active Directory Authentication

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More resources
ClickHouseGoogle Search ApplianceMicrosoft Azure Data Explorer
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