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DBMS > ClickHouse vs. InfluxDB vs. Microsoft Azure Data Explorer vs. Rockset

System Properties Comparison ClickHouse vs. InfluxDB vs. Microsoft Azure Data Explorer vs. Rockset

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonInfluxDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.DBMS for storing time series, events and metricsFully managed big data interactive analytics platformA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedDocument store
Secondary database modelsTime Series DBMSSpatial DBMS infowith GEO packageDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.55
Rank#38  Overall
#23  Relational DBMS
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Websiteclickhouse.comwww.influxdata.com/­products/­influxdb-overviewazure.microsoft.com/­services/­data-explorerrockset.com
Technical documentationclickhouse.com/­docsdocs.influxdata.com/­influxdbdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.rockset.com
DeveloperClickhouse Inc.MicrosoftRockset
Initial release2016201320192019
Current releasev24.4.1.2088-stable, May 20242.7.6, April 2024cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoMIT-License; commercial enterprise version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
  • ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Implementation languageC++GoC++
Server operating systemsFreeBSD
Linux
macOS
Linux
OS X infothrough Homebrew
hostedhosted
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesdynamic typing
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.nonoyesno infoingestion from XML files supported
Secondary indexesyesnoall fields are automatically indexedall fields are automatically indexed
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like query languageKusto Query Language (KQL), SQL subsetRead-only SQL queries, including JOINs
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
HTTP API
JSON over UDP
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Supported programming languagesC# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeskey based and customSharding infoin enterprise version onlySharding infoImplicit feature of the cloud serviceAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.selectable replication factor infoin enterprise version onlyyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.yesyes infoDepending on used storage engineno
User concepts infoAccess controlAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.simple rights management via user accountsAzure Active Directory AuthenticationAccess rights for users and organizations can be defined via Rockset console
More information provided by the system vendor
ClickHouseInfluxDBMicrosoft Azure Data ExplorerRockset
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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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
3rd partiesAiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
» more

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
» more

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

More resources
ClickHouseInfluxDBMicrosoft Azure Data ExplorerRockset
DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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