DBMS > Hazelcast vs. Oracle vs. OrigoDB vs. Realm vs. SWC-DB

System Properties Comparison Hazelcast vs. Oracle vs. OrigoDB vs. Realm vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Widely used RDBMS

A fully ACID in-memory object graph database

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

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store

Relational DBMS

Document store
Object oriented DBMS

Document store

Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Time Series DBMS

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

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

hazelcast.com

www.oracle.com/database

origodb.com

realm.io

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

hazelcast.org/imdg/docs

docs.oracle.com/en/database

origodb.com/docs

realm.io/docs

Developer

Hazelcast

Oracle

Robert Friberg et al

Realm, acquired by MongoDB in May 2019

Alex Kashirin

Initial release

2008

1980

2009

under the name LiveDB

2014

2020

Current release

5.3.6, November 2023

23c, September 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

GPL V3

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 and C++

C++

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
Windows

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

yes

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.NET Client API
HTTP API
LINQ

Proprietary protocol
Thrift

Supported programming languages

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

C++

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

PL/SQL

also stored procedures in Java possible

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Events

yes

Domain Events

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

In-Memory realm

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Role based authorization

yes

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