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DBMS > ClickHouse vs. Google BigQuery vs. NSDb

System Properties Comparison ClickHouse vs. Google BigQuery vs. NSDb

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonNSDb  Xexclude from comparison
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.Large scale data warehouse service with append-only tablesScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.31
Rank#37  Overall
#23  Relational DBMS
Score62.67
Rank#19  Overall
#13  Relational DBMS
Score0.07
Rank#369  Overall
#40  Time Series DBMS
Websiteclickhouse.comcloud.google.com/­bigquerynsdb.io
Technical documentationclickhouse.com/­docscloud.google.com/­bigquery/­docsnsdb.io/­Architecture
DeveloperClickhouse Inc.Google
Initial release201620102017
Current releasev23.12.1.1368-stable, December 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0
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.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
  • 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++Java, Scala
Server operating systemsFreeBSD
Linux
macOS
hostedLinux
macOS
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, string
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 indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)yesSQL-like query language
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
RESTful HTTP/JSON APIgRPC
HTTP REST
WebSocket
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
Java
JavaScript
Objective-C
PHP
Python
Ruby
Java
Scala
Server-side scripts infoStored proceduresyesuser defined functions infoin JavaScriptno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodeskey based and customnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying datano
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Lucene
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 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.Access privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)

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
CData: Connect to Big Data & NoSQL through standard Drivers.
» more

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

More resources
ClickHouseGoogle BigQueryNSDb
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