DBMS > FeatureBase vs. GBase vs. HugeGraph vs. Titan

System Properties Comparison FeatureBase vs. GBase vs. HugeGraph vs. Titan

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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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A fast-speed and highly-scalable Graph DBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Graph DBMS

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

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

www.featurebase.com

www.gbase.cn

github.com/hugegraph
hugegraph.apache.org

github.com/thinkaurelius/titan

Technical documentation

docs.featurebase.com

hugegraph.apache.org/docs

github.com/thinkaurelius/titan/wiki

Developer

Molecula and Pilosa Open Source Contributors

General Data Technology Co., Ltd.

Baidu

Aurelius, owned by DataStax

Initial release

2017

2004

2018

2012

Current release

2022, May 2022

GBase 8a, GBase 8s, GBase 8c

0.9

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

C, Java, Python

Java

Server operating systems

Linux
macOS

Linux

Linux
macOS
Unix

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL queries

Standard with numerous extensions

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Java
Python

Groovy
Java
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

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

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graph

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

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

yes

Users, roles and permissions

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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