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DBMS > Google Cloud Datastore vs. JaguarDB vs. Oracle NoSQL vs. PouchDB

System Properties Comparison Google Cloud Datastore vs. JaguarDB vs. Oracle NoSQL vs. PouchDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonJaguarDB  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformPerformant, highly scalable DBMS for AI and IoT applicationsA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument storeKey-value store
Vector DBMS
Document store
Key-value store
Relational DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.06
Rank#381  Overall
#59  Key-value stores
#15  Vector DBMS
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitecloud.google.com/­datastorewww.jaguardb.comwww.oracle.com/­database/­nosql/­technologies/­nosqlpouchdb.com
Technical documentationcloud.google.com/­datastore/­docswww.jaguardb.com/­support.htmldocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlpouchdb.com/­guides
DeveloperGoogleDataJaguar, Inc.OracleApache Software Foundation
Initial release2008201520112012
Current release3.3 July 202324.1, May 20247.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0Open Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ infothe server part. Clients available in other languagesJavaJavaScript
Server operating systemshostedLinuxLinux
Solaris SPARC/x86
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeyesSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.schema-free
Typing infopredefined data types such as float or dateyes, details hereyesoptionalno
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 indexesyesyesyesyes infovia views
SQL infoSupport of SQLSQL-like query language (GQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C#
Go
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresusing Google App EnginenonoView functions in JavaScript
TriggersCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replicationElectable source-replica replication per shard. Support distributed global deployment with Multi-region table featureMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownowith Hadoop integrationyes
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
Immediate Consistency infodepending on configuration
Eventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoconfigurable infoACID within a storage node (=shard)no
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infooff heap cacheyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsAccess rights for users and rolesno

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More resources
Google Cloud DatastoreJaguarDBOracle NoSQLPouchDB
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