DBMS > GBase vs. GeoMesa vs. HugeGraph

System Properties Comparison GBase vs. GeoMesa vs. HugeGraph

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Editorial information provided by DB-Engines

Name

Description

An analytical database for business intelligence with large customers in China.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A fast-speed and highly-scalable Graph DBMS

Primary database model

Relational DBMS

Spatial DBMS

Graph DBMS

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

Score	1.04
Rank	#190	Overall
	#88	Relational DBMS

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Website

www.gbase.cn

www.geomesa.org

github.com/hugegraph
hugegraph.apache.org

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

hugegraph.apache.org/docs

Developer

CCRi and others

Baidu

Initial release

2014

2018

Current release

GBase 8a

4.0.5, February 2024

0.9

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 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

Scala

Java

Server operating systems

Linux
macOS
Unix

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

SQL

Support of SQL

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Groovy
Java
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Users, roles and permissions

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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