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DBMS > Google Cloud Datastore vs. Graph Engine vs. PouchDB vs. Riak KV

System Properties Comparison Google Cloud Datastore vs. Graph Engine vs. PouchDB vs. Riak KV

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonPouchDB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineJavaScript DBMS with an API inspired by CouchDBDistributed, fault tolerant key-value store
Primary database modelDocument storeGraph DBMS
Key-value store
Document storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score0.56
Rank#241  Overall
#21  Graph DBMS
#34  Key-value stores
Score2.18
Rank#114  Overall
#21  Document stores
Score3.84
Rank#76  Overall
#9  Key-value stores
Websitecloud.google.com/­datastorewww.graphengine.iopouchdb.com
Technical documentationcloud.google.com/­datastore/­docswww.graphengine.io/­docs/­manualpouchdb.com/­guideswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGoogleMicrosoftApache Software FoundationOpenSource, formerly Basho Technologies
Initial release2008201020122009
Current release7.1.1, June 20193.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen SourceOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CJavaScriptErlang
Server operating systemshosted.NETserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesnono
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.nononono
Secondary indexesyesyes infovia viewsrestricted
SQL infoSupport of SQLSQL-like query language (GQL)nonono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
HTTP API
Native Erlang Interface
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
JavaScriptC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresusing Google App EngineyesView functions in JavaScriptErlang
TriggersCallbacks using the Google Apps Enginenoyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infowith a proxy-based framework, named couchdb-loungeSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes, using Riak Security

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More resources
Google Cloud DatastoreGraph Engine infoformer name: TrinityPouchDBRiak KV
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