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DBMS > ClickHouse vs. Hyprcubd vs. InfluxDB

System Properties Comparison ClickHouse vs. Hyprcubd vs. InfluxDB

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonHyprcubd  Xexclude from comparisonInfluxDB  Xexclude from comparison
Hyprcubd 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.Serverless Time Series DBMSDBMS for storing time series, events and metrics
Primary database modelRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsTime Series DBMSSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.20
Rank#37  Overall
#23  Relational DBMS
Score26.56
Rank#28  Overall
#1  Time Series DBMS
Websiteclickhouse.comhyprcubd.com (offline)www.influxdata.com/­products/­influxdb-overview
Technical documentationclickhouse.com/­docsdocs.influxdata.com/­influxdb
DeveloperClickhouse Inc.Hyprcubd, Inc.
Initial release20162013
Current releasev23.12.1.1368-stable, December 20232.7.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoMIT-License; commercial enterprise version available
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.
  • 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.
  • 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.
Implementation languageC++GoGo
Server operating systemsFreeBSD
Linux
macOS
hostedLinux
OS X infothrough Homebrew
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infotime, int, uint, float, stringNumeric data and Strings
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.nonono
Secondary indexesyesnono
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like query languageSQL-like query language
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
gRPC (https)HTTP API
JSON over UDP
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
Server-side scripts infoStored proceduresyesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodeskey based and customSharding infoin enterprise version only
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 only
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesnoyes
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.yesnoyes infoDepending on used storage engine
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.token accesssimple rights management via user accounts
More information provided by the system vendor
ClickHouseHyprcubdInfluxDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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
ClickHouseHyprcubdInfluxDB
DB-Engines blog posts

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

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4 July 2016, Matthias Gelbmann

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

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