DBMS > Datomic vs. HugeGraph vs. Ingres vs. MySQL

System Properties Comparison Datomic vs. HugeGraph vs. Ingres vs. MySQL

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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

A fast-speed and highly-scalable Graph DBMS

Well established RDBMS

Widely used open source RDBMS

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

www.datomic.com

github.com/hugegraph
hugegraph.apache.org

www.actian.com/databases/ingres

www.mysql.com

Technical documentation

docs.datomic.com

hugegraph.apache.org/docs

docs.actian.com/ingres

dev.mysql.com/doc

Developer

Cognitect

Baidu

Actian Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2018

1974

originally developed at University Berkely in early 1970s

1995

Current release

1.0.6735, June 2023

0.9

11.2, May 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

Java

C and C++

Server operating systems

All OS with a Java VM

Linux
macOS
Unix

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
Java

Groovy
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Transaction Functions

asynchronous Gremlin script jobs

yes

proprietary syntax

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

depending on used storage backend, e.g. Cassandra and HBase

Ingres Replicator

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

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

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, roles and permissions

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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