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DBMS > CouchDB vs. Databricks vs. Drizzle vs. Faircom DB

System Properties Comparison CouchDB vs. Databricks vs. Drizzle vs. Faircom DB

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonFaircom DB infoformerly c-treeACE  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.
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.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.
Primary database modelDocument storeDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
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
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Websitecouchdb.apache.orgwww.databricks.comwww.faircom.com/­products/­faircom-db
Technical documentationdocs.couchdb.org/­en/­stabledocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerDatabricksDrizzle project, originally started by Brian AkerFairCom Corporation
Initial release2005201320081979
Current release3.3.3, December 20237.2.4, September 2012V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoGNU GPLcommercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++ANSI C, C++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedFreeBSD
Linux
OS X
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema free, schema optional, schema required, partial schema,
Typing infopredefined data types such as float or datenoyesyes, ANSI SQL Types, JSON, typed binary structures
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.noyesno
Secondary indexesyes infovia viewsyesyesyes
SQL infoSupport of SQLnowith Databricks SQLyes infowith proprietary extensionsyes, ANSI SQL with proprietary extensions
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
JDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
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
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresView functions in JavaScriptuser defined functions and aggregatesnoyes info.Net, JavaScript, C/C++
Triggersyesno infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesMulti-source replication
Source-replica replication
yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACIDACIDtunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesYes, tunable from durable to delayed durability to in-memory
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users can be defined per databasePluggable authentication mechanisms infoe.g. LDAP, HTTPFine grained access rights according to SQL-standard with additional protections for files
More information provided by the system vendor
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatabricksDrizzleFaircom DB infoformerly c-treeACE
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"DatabricksDrizzleFaircom DB infoformerly c-treeACE
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