DBMS > GridGain vs. Hazelcast vs. ObjectBox vs. Realm vs. SQLite

System Properties Comparison GridGain vs. Hazelcast vs. ObjectBox vs. Realm vs. SQLite

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

A widely adopted in-memory data grid

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Widely used embeddable, in-process RDBMS

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Object oriented DBMS
Vector DBMS

Document store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

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

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

www.gridgain.com

hazelcast.com

github.com/objectbox
objectbox.io

realm.io

www.sqlite.org

Technical documentation

www.gridgain.com/docs/index.html

hazelcast.org/imdg/docs

docs.objectbox.io

realm.io/docs

www.sqlite.org/docs.html

Developer

GridGain Systems, Inc.

Hazelcast

ObjectBox Limited

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

Initial release

2007

2008

2017

2014

2000

Current release

GridGain 8.5.1

5.3.6, November 2023

4.0 (May 2024)

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial, open source

Open Source

Apache Version 2; commercial licenses available

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Public Domain

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, Python, REST, SQL

Java

C and C++

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

All OS with a Java VM

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Android
Backend: server-less
iOS
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

yes

not rigid because of 'dynamic typing' concept.

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

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JCache
JPA
Memcached protocol
RESTful HTTP API

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

.Net
Java

with Android only
Objective-C
React Native
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

Event Listeners, Executor Services

runs within the applications so server-side scripts are unnecessary

Triggers

yes (cache interceptors and events)

yes

Events

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Replicated Map

Data sync between devices allowing occasional connected databases to work completely offline

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

In-Memory realm

yes

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

Role-based access control

yes

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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