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DBMS > CouchDB vs. Google Cloud Datastore vs. Manticore Search vs. RDFox

System Properties Comparison CouchDB vs. Google Cloud Datastore vs. Manticore Search vs. RDFox

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.High performance knowledge graph and semantic reasoning engine
Primary database modelDocument storeDocument storeSearch engineGraph DBMS
RDF store
Secondary database modelsSpatial DBMS infousing the Geocouch extensionTime Series DBMS infousing the Manticore Columnar LibraryRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitecouchdb.apache.orgcloud.google.com/­datastoremanticoresearch.comwww.oxfordsemantic.tech
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsmanual.manticoresearch.comdocs.oxfordsemantic.tech
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleManticore SoftwareOxford Semantic Technologies
Initial release2005200820172017
Current release3.3.3, December 20236.0, February 20236.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++C++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedFreeBSD
Linux
macOS
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-freeFixed schemayes infoRDF schemas
Typing infopredefined data types such as float or datenoyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XML
Secondary indexesyes infovia viewsyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP API
SPARQL 1.1
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
Java
Server-side scripts infoStored proceduresView functions in JavaScriptusing Google App Engineuser defined functions
TriggersyesCallbacks using the Google Apps Engineno
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
Multi-source replication using PaxosSynchronous replication based on Galera libraryreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
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 databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noRoles, resources, and access types

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More resources
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreManticore SearchRDFox
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