DBMS > H2 vs. HugeGraph vs. mSQL vs. TigerGraph vs. Titan

System Properties Comparison H2 vs. HugeGraph vs. mSQL vs. TigerGraph vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A fast-speed and highly-scalable Graph DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.h2database.com

github.com/hugegraph
hugegraph.apache.org

hughestech.com.au/products/msql

www.tigergraph.com

github.com/thinkaurelius/titan

Technical documentation

www.h2database.com/html/main.html

hugegraph.apache.org/docs

docs.tigergraph.com

github.com/thinkaurelius/titan/wiki

Developer

Thomas Mueller

Baidu

Hughes Technologies

Aurelius, owned by DataStax

Initial release

2005

2018

1994

2017

2012

Current release

2.2.220, July 2023

0.9

4.4, October 2021

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2.0

commercial

free licenses can be provided

commercial

Open Source

Apache license, version 2.0

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

C++

Java

Server operating systems

All OS with a Java VM

Linux
macOS
Unix

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

Linux

Linux
OS X
Unix
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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Java

Groovy
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

C++
Java

Clojure
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

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

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

yes

Relationships in graph

Transaction concepts

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

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

Role-based access control

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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