DBMS > EsgynDB vs. H2 vs. Hive vs. HugeGraph vs. jBASE

System Properties Comparison EsgynDB vs. H2 vs. Hive vs. HugeGraph vs. jBASE

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A fast-speed and highly-scalable Graph DBMS

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Relational DBMS

Graph DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Website

www.esgyn.cn

www.h2database.com

hive.apache.org

github.com/hugegraph
hugegraph.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

www.h2database.com/html/main.html

cwiki.apache.org/confluence/display/Hive/Home

hugegraph.apache.org/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Esgyn

Thomas Mueller

Apache Software Foundation

initially developed by Facebook

Baidu

Rocket Software (formerly Zumasys)

Initial release

2015

2005

2012

2018

1991

Current release

2.2.220, July 2023

3.1.3, April 2022

0.9

5.7

License

Commercial or Open Source

commercial

Open Source

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

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

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

Java

Server operating systems

Linux

All OS with a Java VM

Linux
macOS
Unix

AIX
Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

Embedded SQL for jBASE in BASIC

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

JDBC
ODBC
Thrift

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java

C++
Java
PHP
Python

Groovy
Java
Python

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Java Stored Procedures and User-Defined Functions

yes

user defined functions and integration of map-reduce

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

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

selectable replication factor

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

Users, roles and permissions

Access rights can be defined down to the item level

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