DBMS > Fauna vs. IBM Cloudant vs. JaguarDB vs. Microsoft Azure Cosmos DB vs. TigerGraph

System Properties Comparison Fauna vs. IBM Cloudant vs. JaguarDB vs. Microsoft Azure Cosmos DB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

Globally distributed, horizontally scalable, multi-model database service

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store

Key-value store
Vector DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

fauna.com

www.ibm.com/products/cloudant

www.jaguardb.com

azure.microsoft.com/services/cosmos-db

www.tigergraph.com

Technical documentation

docs.fauna.com

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

learn.microsoft.com/azure/cosmos-db

docs.tigergraph.com

Developer

Fauna, Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Microsoft

Initial release

2014

2010

2015

2014

2017

Current release

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

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

Scala

Erlang

C++

the server part. Clients available in other languages

C++

Server operating systems

hosted

Linux

hosted

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

View functions (Map-Reduce) in JavaScript

JavaScript

yes

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

Multi-source replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Identity management, authentication, and access control

Access rights for users can be defined per database

rights management via user accounts

Access rights can be defined down to the item level

Role-based access control

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