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DBMS > Apache Druid vs. CouchDB vs. CrateDB

System Properties Comparison Apache Druid vs. CouchDB vs. CrateDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonCrateDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Distributed Database based on Lucene
Primary database modelRelational DBMS
Time Series DBMS
Document storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score10.26
Rank#45  Overall
#7  Document stores
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Websitedruid.apache.orgcouchdb.apache.orgcratedb.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.couchdb.org/­en/­stablecratedb.com/­docs
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerCrate
Initial release201220052013
Current release29.0.1, April 20243.3.3, December 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache version 2Open Source
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaErlangJava
Server operating systemsLinux
OS X
Unix
Android
BSD
Linux
OS X
Solaris
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support
Data schemeyes infoschema-less columns are supportedschema-freeFlexible Schema (defined schema, partial schema, schema free)
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 indexesyesyes infovia viewsyes
SQL infoSupport of SQLSQL for queryingnoyes, but no triggers and constraints, and PostgreSQL compatibility
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP/JSON APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Server-side scripts infoStored proceduresnoView functions in JavaScriptuser defined functions (Javascript)
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoimproved architecture with release 2.0Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Configurable replication on table/partition-level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleno infounique row identifiers can be used for implementing an optimistic concurrency control strategy
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyes
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.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users can be defined per databaserights management via user accounts
More information provided by the system vendor
Apache DruidCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"CrateDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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Apache DruidCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"CrateDB
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