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DBMS > ClickHouse vs. Drizzle vs. Spark SQL

System Properties Comparison ClickHouse vs. Drizzle vs. Spark SQL

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonDrizzle  Xexclude from comparisonSpark SQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionColumn-oriented Relational DBMS powering YandexMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.68
Rank#45  Overall
#29  Relational DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Websiteclickhouse.techspark.apache.org/­sql
Technical documentationclickhouse.tech/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperYandex LLCDrizzle project, originally started by Brian AkerApache Software Foundation
Initial release201620082014
Current releasev20.11.3.3-stable, November 20207.2.4, September 20123.1.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGNU GPLOpen 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++C++Scala
Server operating systemsFreeBSD
Linux
macOS
FreeBSD
Linux
OS X
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesnoyesno
SQL infoSupport of SQLClose to ANSI SQLyes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsHTTP REST
JDBC
ODBC
Proprietary protocol
JDBCJDBC
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
C++
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnono infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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 rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPno

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3rd partiesSQLFlow: Provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across Databases, ETL, Business Intelligence, Cloud and Hadoop environments by parsing SQL Script and stored procedure.
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More resources
ClickHouseDrizzleSpark SQL
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