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DBMS > Couchbase vs. Datomic vs. Greenplum vs. MongoDB vs. Solr

System Properties Comparison Couchbase vs. Datomic vs. Greenplum vs. MongoDB vs. Solr

Editorial information provided by DB-Engines
NameCouchbase infoOriginally called Membase  Xexclude from comparisonDatomic  Xexclude from comparisonGreenplum  Xexclude from comparisonMongoDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile databaseDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeRelational DBMSRelational DBMSDocument storeSearch engine
Secondary database modelsKey-value store infooriginating from the former Membase product and supporting the Memcached protocol
Spatial DBMS infousing the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS
Document store
Spatial DBMS
Spatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.30
Rank#36  Overall
#5  Document stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score421.65
Rank#5  Overall
#1  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.couchbase.comwww.datomic.comgreenplum.orgwww.mongodb.comsolr.apache.org
Technical documentationdocs.couchbase.comdocs.datomic.comdocs.greenplum.orgwww.mongodb.com/­docs/­manualsolr.apache.org/­resources.html
DeveloperCouchbase, Inc.CognitectPivotal Software Inc.MongoDB, IncApache Software Foundation
Initial release20112012200520092006
Current releaseServer: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 20231.0.6735, June 20237.0.0, September 20236.0.7, June 20239.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoBusiness Source License (BSL 1.1); Commercial licenses also availablecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono infoMongoDB available as DBaaS (MongoDB Atlas)no
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Implementation languageC, C++, Go and ErlangJava, ClojureC++Java
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinuxLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes infosupports customizable data types and automatic typing
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.noyes infosince Version 4.2yes
Secondary indexesyesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use casesnoyesRead-only SQL queries via the MongoDB Atlas SQL InterfaceSolr Parallel SQL Interface
APIs and other access methodsCLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data
RESTful HTTP APIJDBC
ODBC
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
Go
Java
JavaScript infoNode.js
Kotlin
PHP
Python
Ruby
Scala
Clojure
Java
C
Java
Perl
Python
R
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresFunctions and timers in JavaScript and UDFs in Java, Python, SQL++yes infoTransaction FunctionsyesJavaScriptJava plugins
Triggersyes infovia the TAP protocolBy using transaction functionsyesyes infoin MongoDB Atlas onlyyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesAutomatic Shardingnone infoBut extensive use of caching in the application peersShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infoincluding cross data center replication
Source-replica replication
none infoBut extensive use of caching in the application peersSource-replica replicationMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infoselectable on a per-operation basis
Immediate ConsistencyImmediate ConsistencyEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Eventual Consistency
Foreign keys infoReferential integritynonoyesno infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDMulti-document ACID Transactions with snapshot isolationoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infooptional, enabled by defaultyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoEphemeral bucketsyes inforecommended only for testing and developmentnoyes infoIn-memory storage engine introduced with MongoDB version 3.2yes
User concepts infoAccess controlUser and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.nofine grained access rights according to SQL-standardAccess rights for users and rolesyes
More information provided by the system vendor
Couchbase infoOriginally called MembaseDatomicGreenplumMongoDBSolr
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsHundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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Couchbase infoOriginally called MembaseDatomicGreenplumMongoDBSolr
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