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DBMS > ClickHouse vs. Riak KV vs. Spark SQL

System Properties Comparison ClickHouse vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionColumn-oriented Relational DBMS powering YandexDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.59
Rank#46  Overall
#29  Relational DBMS
Score5.10
Rank#68  Overall
#9  Key-value stores
Score21.39
Rank#34  Overall
#20  Relational DBMS
Websiteclickhouse.techriak.com/­products/­riak-kvspark.apache.org/­sql
Technical documentationclickhouse.tech/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperYandex LLCBasho TechnologiesApache Software Foundation
Initial release201620092014
Current releasev20.11.3.3-stable, November 20202.1.0, April 20153.1.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangScala
Server operating systemsFreeBSD
Linux
macOS
Linux
OS X
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesnorestrictedno
SQL infoSupport of SQLClose to ANSI SQLnoSQL-like DML and DDL statements
APIs and other access methodsHTTP REST
JDBC
ODBC
Proprietary protocol
HTTP API
Native Erlang Interface
JDBC
ODBC
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
Scala info3rd party library
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJavaScript and Erlangno
Triggersnoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesno
User concepts infoAccess controlAccess rights for users and rolesnono

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More resources
ClickHouseRiak KVSpark SQL
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