DBMS > GBase vs. Graph Engine vs. Hazelcast vs. VoltDB

System Properties Comparison GBase vs. Graph Engine vs. Hazelcast vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A widely adopted in-memory data grid

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

Technical documentation

www.graphengine.io/docs/manual

hazelcast.org/imdg/docs

docs.voltdb.com

Developer

General Data Technology Co., Ltd.

Microsoft

Hazelcast

VoltDB Inc.

Initial release

2004

2010

2008

2010

Current release

GBase 8a, GBase 8s, GBase 8c

5.3.6, November 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2; commercial licenses available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

.NET and C

Java

Java, C++

Server operating systems

Linux

.NET

All OS with a Java VM

Linux
OS X

for development

Data scheme

yes

schema-free

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C#
C++
F#
Visual Basic

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Event Listeners, Executor Services

Java

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication
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

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Snapshots and command logging

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

Role-based access control

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Trinity
30 October 2010, microsoft.com

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019
27 February 2019, Data Science Central

provided by Google News

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Hazelcast Expands Global Partner Program to Support Mission-Critical, AI Application Projects
20 August 2024, PR Newswire

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
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Hazelcast Showcases Real-Time Data Platform at 2024 Gartner Summit
15 May 2024, Datanami

Hazelcast appoints Anthony Griffin as Chief Architect -
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VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

Unveiling Volt Active Data’s game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Announces Key New Hires
26 October 2021, citybiz

Solutions Review Sits Down with VoltDB CEO David Flower
17 April 2018, Solutions Review

VoltDB Aims for Fast Big Data Development
29 January 2015, ADT Magazine

provided by Google News

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