DBMS > Datomic vs. Ignite vs. Microsoft Azure Cosmos DB vs. NuoDB vs. RDF4J

System Properties Comparison Datomic vs. Ignite vs. Microsoft Azure Cosmos DB vs. NuoDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Globally distributed, horizontally scalable, multi-model database service

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

RDF store

Secondary database models

Spatial DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

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

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.datomic.com

ignite.apache.org

azure.microsoft.com/services/cosmos-db

www.3ds.com/nuodb-distributed-sql-database

rdf4j.org

Technical documentation

docs.datomic.com

apacheignite.readme.io/docs

learn.microsoft.com/azure/cosmos-db

doc.nuodb.com

rdf4j.org/documentation

Developer

Cognitect

Apache Software Foundation

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

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

Initial release

2012

2015

2014

2013

2004

Current release

1.0.6735, June 2023

Apache Ignite 2.6

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

commercial

limited edition free

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++, Java, .Net

C++

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Clojure
Java

C#
C++
Java
PHP
Python
Ruby
Scala

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

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes (compute grid and cache interceptors can be used instead)

JavaScript

Java, SQL

yes

Triggers

By using transaction functions

yes (cache interceptors and events)

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes (replicated cache)

yes

Implicit feature of the cloud service

yes

Managed transparently by NuoDB

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

tunable commit protocol

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

Temporary table

User concepts

Access control

Security Hooks for custom implementations

Access rights can be defined down to the item level

Standard SQL roles/ privileges, Administrative Users

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