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DBMS > ClickHouse vs. Memcached vs. Microsoft Azure Data Explorer vs. ToroDB vs. VictoriaMetrics

System Properties Comparison ClickHouse vs. Memcached vs. Microsoft Azure Data Explorer vs. ToroDB vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonToroDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.In-memory key-value store, originally intended for cachingFully managed big data interactive analytics platformA MongoDB-compatible JSON document store, built on top of PostgreSQLA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSKey-value storeRelational DBMS infocolumn orientedDocument storeTime Series DBMS
Secondary database modelsTime Series DBMSDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.20
Rank#37  Overall
#23  Relational DBMS
Score20.74
Rank#32  Overall
#4  Key-value stores
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score1.42
Rank#161  Overall
#14  Time Series DBMS
Websiteclickhouse.comwww.memcached.orgazure.microsoft.com/­services/­data-explorergithub.com/­torodb/­servervictoriametrics.com
Technical documentationclickhouse.com/­docsgithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­en-us/­azure/­data-explorerdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperClickhouse Inc.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoft8KdataVictoriaMetrics
Initial release20162003201920162018
Current releasev24.3.2.23-lts, April 20241.6.25, March 2024cloud service with continuous releasesv1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBSD licensecommercialOpen Source infoAGPL-V3Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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++CJavaGo
Server operating systemsFreeBSD
Linux
macOS
FreeBSD
Linux
OS X
Unix
Windows
hostedAll OS with a Java 7 VMFreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infostring, integer, double, boolean, date, object_id
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.noyesnono
Secondary indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)noKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
Proprietary protocolMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
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
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodeskey based and customnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.none infoRepcached, a Memcached patch, provides this functionallityyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSynchronous replication
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
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes
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 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.yes infousing SASL (Simple Authentication and Security Layer) protocolAzure Active Directory AuthenticationAccess rights for users and roles

More information provided by the system vendor

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Related products and services
3rd partiesDoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
» more

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
» more

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

More resources
ClickHouseMemcachedMicrosoft Azure Data ExplorerToroDBVictoriaMetrics
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