DBMS > Fujitsu Enterprise Postgres vs. InterSystems IRIS vs. JanusGraph vs. MongoDB vs. TimesTen

System Properties Comparison Fujitsu Enterprise Postgres vs. InterSystems IRIS vs. JanusGraph vs. MongoDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Graph DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.postgresql.fastware.com

www.intersystems.com/products/intersystems-iris

janusgraph.org

www.mongodb.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.postgresql.fastware.com/product-manuals

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

docs.janusgraph.org

www.mongodb.com/docs/manual

docs.oracle.com/database/timesten-18.1

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

InterSystems

Linux Foundation; originally developed as Titan by Aurelius

MongoDB, Inc

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2017

2009

1998

Current release

Fujitsu Enterprise Postgres 14, January 2022

2023.3, June 2023

0.6.3, February 2023

6.0.7, June 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java

C++

Server operating systems

Linux
Windows

AIX
Linux
macOS
Ubuntu
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

depending on used data model

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
C++
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

JavaScript

PL/SQL

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

optional, enabled by default

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

User authentification and security via Rexster Graph Server

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

Core based licensing
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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