DBMS > Google BigQuery vs. jBASE vs. PouchDB vs. RethinkDB

System Properties Comparison Google BigQuery vs. jBASE vs. PouchDB vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A robust multi-value DBMS comprising development tools and middleware

JavaScript DBMS with an API inspired by CouchDB

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Relational DBMS

Multivalue DBMS

Document store

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

cloud.google.com/bigquery

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

pouchdb.com

rethinkdb.com

Technical documentation

cloud.google.com/bigquery/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

pouchdb.com/guides

rethinkdb.com/docs

Developer

Google

Rocket Software (formerly Zumasys)

Apache Software Foundation

The Linux Foundation

since July 2017

Initial release

2010

1991

2012

2009

Current release

5.7

7.1.1, June 2019

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Server operating systems

hosted

AIX
Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

string, binary, float, bool, date, geometry

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Basic
Jabbascript
Java

JavaScript

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

View functions in JavaScript

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights can be defined down to the item level

yes

users and table-level permissions

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