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DBMS > ClickHouse vs. Google BigQuery vs. Google Cloud Bigtable vs. MySQL

System Properties Comparison ClickHouse vs. Google BigQuery vs. Google Cloud Bigtable vs. MySQL

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionColumn-oriented Relational DBMS powering YandexLarge scale data warehouse service with append-only tablesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Widely used open source RDBMS
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS infoKey/Value like access via memcached API
Secondary database modelsTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.88
Rank#44  Overall
#28  Relational DBMS
Score54.13
Rank#22  Overall
#15  Relational DBMS
Score5.24
Rank#80  Overall
#12  Key-value stores
#6  Wide column stores
Score1205.54
Rank#2  Overall
#2  Relational DBMS
Websiteclickhouse.techcloud.google.com/­bigquerycloud.google.com/­bigtablewww.mysql.com
Technical documentationclickhouse.tech/­docscloud.google.com/­bigquery/­docscloud.google.com/­bigtable/­docsdev.mysql.com/­doc
DeveloperClickhouse Inc.GoogleGoogleOracle infosince 2010, originally MySQL AB, then Sun
Initial release2016201020151995
Current releasev22.8.5.29-lts, September 20228.0.31, October 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ScaleGrid for MySQL: Fully managed MySQL hosting On-Premises and on a wide variety of cloud providers. Easily deploy, monitor, provision, and scale your deployments in the cloud.
Implementation languageC++C and C++
Server operating systemsFreeBSD
Linux
macOS
hostedhostedFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nononoyes
Secondary indexesyes, when using the MergeTree enginenonoyes
SQL infoSupport of SQLClose to ANSI SQLyesnoyes infowith proprietary extensions
APIs and other access methodsHTTP REST
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
Proprietary native API
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
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptnoyes infoproprietary syntax
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying dataAtomic single-row operationsACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.yesnonoyes
User concepts infoAccess controlAccess rights for users and rolesAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept infono user groups or roles

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More resources
ClickHouseGoogle BigQueryGoogle Cloud BigtableMySQL
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