DBMS > Cassandra vs. Datomic vs. Hazelcast vs. Microsoft Azure AI Search

System Properties Comparison Cassandra vs. Datomic vs. Hazelcast vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A widely adopted in-memory data grid

Search-as-a-service for web and mobile app development

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Document store

JSON support with IMDG 3.12

Vector DBMS

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

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Website

cassandra.apache.org

www.datomic.com

hazelcast.com

azure.microsoft.com/en-us/services/search

Technical documentation

cassandra.apache.org/doc/latest

docs.datomic.com

hazelcast.org/imdg/docs

learn.microsoft.com/en-us/azure/search

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Cognitect

Hazelcast

Microsoft

Initial release

2008

2012

2008

2015

Current release

4.1.3, July 2023

1.0.7075, December 2023

5.3.6, November 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

limited edition free

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

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

Java, Clojure

Java

Server operating systems

BSD
Linux
OS X
Windows

All OS with a Java VM

hosted

Data scheme

schema-free

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

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

RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Clojure
Java

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

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Event Listeners, Executor Services

Triggers

yes

By using transaction functions

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

none

But extensive use of caching in the application peers

yes

Replicated Map

yes

Implicit feature of the cloud service

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users can be defined per object

Role-based access control

yes

using Azure authentication

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

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

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11 June 2024

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7 June 2024

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5 June 2024

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3 June 2024

Focus on Creativity, Not Clusters: DataStax Mission Control in Action!
30 May 2024

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