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DBMS > CouchDB vs. Databricks vs. GridGain vs. Sphinx

System Properties Comparison CouchDB vs. Databricks vs. GridGain vs. Sphinx

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  Xexclude from comparison
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.GridGain is an in-memory computing platform, built on Apache IgniteOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument store
Relational DBMS
Key-value store
Relational DBMS
Search engine
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.30
Rank#45  Overall
#7  Document stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecouchdb.apache.orgwww.databricks.comwww.gridgain.comsphinxsearch.com
Technical documentationdocs.couchdb.org/­en/­stabledocs.databricks.comwww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerDatabricksGridGain Systems, Inc.Sphinx Technologies Inc.
Initial release2005201320072001
Current release3.3.3, December 2023GridGain 8.5.13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJava, C++, .NetC++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or datenoyesno
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 viewsyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnowith Databricks SQLANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol
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
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresView functions in JavaScriptuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)no
Triggersyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 databaseSecurity Hooks for custom implementationsno
More information provided by the system vendor
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatabricksGridGainSphinx
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"DatabricksGridGainSphinx
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