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

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

Editorial information provided by DB-Engines

Name

Description

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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A widely adopted in-memory data grid

RDBMS for high security requirements

Primary database model

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	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

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

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Website

Technical documentation

www.h2database.com/html/main.html

docs.harperdb.io/docs

hazelcast.org/imdg/docs

Developer

General Data Technology Co., Ltd.

Thomas Mueller

HarperDB

Hazelcast

relex.ru

Initial release

2004

2005

2017

2008

1990

Current release

GBase 8a, GBase 8s, GBase 8c

2.2.220, July 2023

3.1, August 2021

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

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

commercial

free community edition available

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, Java, Python

Java

Node.js

Java

C and C++

Server operating systems

Linux

All OS with a Java VM

Linux
OS X

All OS with a Java VM

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

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL

Support of SQL

Standard with numerous extensions

yes

SQL-like data manipulation statements

SQL-like query language

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JCache
JPA
Memcached protocol
RESTful HTTP API

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

Supported programming languages

Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.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

Custom Functions

since release 3.1

yes

Event Listeners, Executor Services

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

the nodes on which a table resides can be defined

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

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

Atomic execution of specific operations

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

Role-based access control

fine grained access rights according to SQL-standard

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