DBMS > GigaSpaces vs. Hazelcast vs. Machbase Neo

System Properties Comparison GigaSpaces vs. Hazelcast vs. Machbase Neo

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A widely adopted in-memory data grid

TimeSeries DBMS for AIoT and BigData

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Time Series DBMS

Secondary database models

Graph DBMS
Search engine

Document store

JSON support with IMDG 3.12

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

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	0.22
Rank	#324	Overall
	#29	Time Series DBMS

Website

www.gigaspaces.com

hazelcast.com

machbase.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

hazelcast.org/imdg/docs

machbase.com/dbms

Developer

Gigaspaces Technologies

Hazelcast

Machbase

Initial release

2000

2008

2013

Current release

15.5, September 2020

5.3.6, November 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2; commercial licenses available

commercial

free test version available

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

Java, C++, .Net

Java

Server operating systems

Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux
macOS
Windows

Data scheme

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.

XML can be used for describing objects metadata

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JCache
JPA
Memcached protocol
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

yes, event driven architecture

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

Replicated Map

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

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.

yes

volatile and lookup table

User concepts

Access control

Role-based access control

simple password-based access control

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More resources

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