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DBMS > CouchDB vs. Databricks vs. Drizzle vs. FatDB vs. TimescaleDB

System Properties Comparison CouchDB vs. Databricks vs. Drizzle vs. FatDB vs. TimescaleDB

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonTimescaleDB  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.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .NET NoSQL DBMS that can integrate with and extend SQL Server.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument storeDocument store
Relational DBMS
Relational DBMSDocument store
Key-value store
Time Series DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitecouchdb.apache.orgwww.databricks.comwww.timescale.com
Technical documentationdocs.couchdb.org/­en/­stabledocs.databricks.comdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerDatabricksDrizzle project, originally started by Brian AkerFatCloudTimescale
Initial release20052013200820122017
Current release3.3.3, December 20237.2.4, September 20122.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++C#C
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedFreeBSD
Linux
OS X
WindowsLinux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesyes
Secondary indexesyes infovia viewsyesyesyesyes
SQL infoSupport of SQLnowith Databricks SQLyes infowith proprietary extensionsno infoVia inetgration in SQL Serveryes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
JDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Python
R
Scala
C
C++
Java
PHP
C#.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresView functions in JavaScriptuser defined functions and aggregatesnoyes infovia applicationsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesno infohooks for callbacks inside the server can be used.yes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesMulti-source replication
Source-replica replication
selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users can be defined per databasePluggable authentication mechanisms infoe.g. LDAP, HTTPno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standard
More information provided by the system vendor
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatabricksDrizzleFatDBTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatabricksDrizzleFatDBTimescaleDB
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