DBMS > Cassandra vs. Hazelcast vs. Oracle Coherence vs. Realm

System Properties Comparison Cassandra vs. Hazelcast vs. Oracle Coherence vs. Realm

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A widely adopted in-memory data grid

Oracles in-memory data grid solution

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

Primary database model

Wide column store

Key-value store

Document store

Secondary database models

Vector DBMS

starting with release V5

Document store

JSON support with IMDG 3.12

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

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

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

cassandra.apache.org

hazelcast.com

www.oracle.com/java/coherence

realm.io

Technical documentation

cassandra.apache.org/doc/latest

hazelcast.org/imdg/docs

docs.oracle.com/en/middleware/standalone/coherence

realm.io/docs

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Hazelcast

Oracle

Realm, acquired by MongoDB in May 2019

Initial release

2008

2007

2014

Current release

4.1.3, July 2023

5.3.6, November 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Server operating systems

BSD
Linux
OS X
Windows

All OS with a Java VM

Android
Backend: server-less
iOS
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.

yes

the object must implement a serialization strategy

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

SQL-like query language

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JCache
JPA
Memcached protocol
RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

.Net
C++
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Events

yes

Live Events

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

Replicated Map

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

Access rights for users can be defined per object

Role-based access control

authentification to access the cache via certificates or http basic authentication

yes

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

How Concide Built its Chat Platform with Enhanced Document Management for Legal Tech Professionals
23 May 2024

Astra Vectorize: Generate Vector Embeddings with 1 Line of Code
22 May 2024

GitHub Copilot + DataStax Astra DB: Build GenAI Apps 100x Faster
21 May 2024

Empowering On-Premises Deployments with Generative AI: Introducing Vector Search for a Self-Managed Modern Architecture
15 May 2024

Tips and Tricks for the DataStax Astra CLI
7 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.