DBMS > EXASOL vs. HBase vs. IRONdb vs. MongoDB vs. RDF4J

System Properties Comparison EXASOL vs. HBase vs. IRONdb vs. MongoDB vs. RDF4J

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Wide-column store based on Apache Hadoop and on concepts of BigTable

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

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	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.exasol.com

hbase.apache.org

www.circonus.com/solutions/time-series-database/

www.mongodb.com

rdf4j.org

Technical documentation

www.exasol.com/resources

hbase.apache.org/book.html

docs.circonus.com/irondb/category/getting-started

www.mongodb.com/docs/manual

rdf4j.org/documentation

Developer

Exasol

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Circonus LLC.

MongoDB, Inc

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2000

2008

2017

2009

2004

Current release

2.3.4, January 2021

V0.10.20, January 2018

6.0.7, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

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

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

Java

C and C++

C++

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free, schema definition possible

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

RDF Schemas

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

text, numeric, histograms

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

Java API
RESTful HTTP API
Thrift

HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java
Lua
Python
R

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Coprocessors in Java

yes, in Lua

JavaScript

yes

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

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

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

Multi-document ACID Transactions with snapshot isolation

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

in-memory storage is supported as well

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

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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

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

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

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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