DBMS > Bangdb vs. GBase vs. H2 vs. Hazelcast vs. Linter

System Properties Comparison Bangdb vs. GBase vs. H2 vs. Hazelcast vs. Linter

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

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

A widely adopted in-memory data grid

RDBMS for high security requirements

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Website

Technical documentation

docs.bangdb.com

www.h2database.com/html/main.html

hazelcast.org/imdg/docs

Developer

Sachin Sinha, BangDB

General Data Technology Co., Ltd.

Thomas Mueller

Hazelcast

relex.ru

Initial release

2012

2004

2005

2008

1990

Current release

BangDB 2.0, October 2021

GBase 8a, GBase 8s, GBase 8c

2.2.220, July 2023

5.3.6, November 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

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

Open Source

Apache Version 2; commercial licenses available

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, C++

C, Java, Python

Java

C and C++

Server operating systems

Linux

All OS with a Java VM

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

the object must implement a serialization strategy

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

Standard with numerous extensions

yes

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
Python

Java

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

yes

Event Listeners, Executor Services

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes, Notifications (with Streaming only)

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

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

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

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

yes

Replicated Map

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

yes

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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