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DBMS > Apache Druid vs. ClickHouse vs. Databricks

System Properties Comparison Apache Druid vs. ClickHouse vs. Databricks

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonClickHouse  Xexclude from comparisonDatabricks  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA 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.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Relational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.18
Rank#84  Overall
#45  Relational DBMS
#7  Time Series DBMS
Score18.77
Rank#31  Overall
#19  Relational DBMS
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Websitedruid.apache.orgclickhouse.comwww.databricks.com
Technical documentationdruid.apache.org/­docs/­latest/­designclickhouse.com/­docsdocs.databricks.com
DeveloperApache Software Foundation and contributorsClickhouse Inc.Databricks
Initial release201220162013
Current release30.0.0, June 2024v24.6.2.17-stable, July 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
macOS
hosted
Data schemeyes infoschema-less columns are supportedyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes
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.nonoyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL for queryingClose to ANSI SQL (SQL/JSON + extensions)with Databricks SQL
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C# 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
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser defined functions and aggregates
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedkey based and custom
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess 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.

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Apache DruidClickHouseDatabricks
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