DBMS > 4D vs. Datomic vs. Graph Engine vs. Hazelcast

System Properties Comparison 4D vs. Datomic vs. Graph Engine vs. Hazelcast

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A widely adopted in-memory data grid

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Website

Technical documentation

developer.4d.com

docs.datomic.com

www.graphengine.io/docs/manual

hazelcast.org/imdg/docs

Developer

4D, Inc

Cognitect

Microsoft

Hazelcast

Initial release

1984

2012

2010

2008

Current release

v20, April 2023

1.0.7075, December 2023

5.3.6, November 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

MIT License

Open Source

Apache Version 2; commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Clojure

.NET and C

Java

Server operating systems

OS X
Windows

All OS with a Java VM

.NET

All OS with a Java VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

Clojure
Java

C#
C++
F#
Visual Basic

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Event Listeners, Executor Services

Triggers

yes

By using transaction functions

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

But extensive use of caching in the application peers

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

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

User concepts

Access control

Users and groups

Role-based access control

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More resources

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