DBMS > CouchDB vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Cosmos DB vs. Newts vs. TigerGraph

System Properties Comparison CouchDB vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Cosmos DB vs. Newts vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS based on Cassandra

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

Primary database model

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

couchdb.apache.org

www.postgresql.fastware.com

azure.microsoft.com/services/cosmos-db

opennms.github.io/newts

www.tigergraph.com

Technical documentation

docs.couchdb.org/en/stable

www.postgresql.fastware.com/product-manuals

learn.microsoft.com/azure/cosmos-db

github.com/OpenNMS/newts/wiki

docs.tigergraph.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Microsoft

OpenNMS Group

Initial release

2005

2014

2017

Current release

3.3.3, December 2023

Fujitsu Enterprise Postgres 14, January 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

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

Erlang

Java

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Linux
OS X
Windows

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

via views

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

HTTP REST
Java API

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

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Java

C++
Java

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

JavaScript

yes

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

partitioning by range, list and by hash

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

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

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

atomic operations within a single document possible

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes, multi-version concurrency control (MVCC)

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Role-based access control

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
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Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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