DBMS > Google BigQuery vs. IBM Cloudant vs. JaguarDB vs. JSqlDb

System Properties Comparison Google BigQuery vs. IBM Cloudant vs. JaguarDB vs. JSqlDb

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Large scale data warehouse service with append-only tables

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Relational DBMS

Document store

Key-value store
Vector DBMS

Document store
Object oriented DBMS

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/cloudant

www.jaguardb.com

jsqldb.org (offline)

Technical documentation

cloud.google.com/bigquery/docs

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

Developer

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Konrad von Backstrom

Initial release

2010

2015

2018

Current release

3.3 July 2023

0.8, December 2018

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

the server part. Clients available in other languages

Server operating systems

hosted

Linux

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions (Map-Reduce) in JavaScript

functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

none

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

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

using RocksDB

In-memory capabilities

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

rights management via user accounts

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