DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google Cloud Datastore vs. jBASE vs. PouchDB vs. Vitess

System Properties Comparison Google Cloud Datastore vs. jBASE vs. PouchDB vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonjBASE  Xexclude from comparisonPouchDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA robust multi-value DBMS comprising development tools and middlewareJavaScript DBMS with an API inspired by CouchDBScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument storeMultivalue DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecloud.google.com/­datastorewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasepouchdb.comvitess.io
Technical documentationcloud.google.com/­datastore/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9pouchdb.com/­guidesvitess.io/­docs
DeveloperGoogleRocket Software (formerly Zumasys)Apache Software FoundationThe Linux Foundation, PlanetScale
Initial release2008199120122013
Current release5.77.1.1, June 201915.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache Version 2.0, commercial licenses available
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 languageJavaScriptGo
Server operating systemshostedAIX
Linux
Windows
server-less, requires a JavaScript environment (browser, Node.js)Docker
Linux
macOS
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereoptionalnoyes
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.noyesno
Secondary indexesyesyes infovia viewsyes
SQL infoSupport of SQLSQL-like query language (GQL)Embedded SQL for jBASE in BASICnoyes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
HTTP REST infoonly for PouchDB Server
JavaScript API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
JavaScriptAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App EngineyesView functions in JavaScriptyes infoproprietary syntax
TriggersCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesno
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 across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes 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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelnoUsers with fine-grained authorization concept infono user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google Cloud DatastorejBASEPouchDBVitess
DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Recent citations in the news

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
21 May 2024, TechRadar

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

Inside Google’s strategic move to eliminate customer cloud data transfer fees
12 January 2024, Network World

Why Google is waiving egress fees for disgruntled customers ditching GCP
11 January 2024, The Register

provided by Google News

Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, IBM

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

PlanetScale Serves up Vitess-Powered Serverless MySQL
23 November 2021, The New Stack

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News



Share this page

Featured Products

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

Present your product here