DBMS > Hazelcast vs. HEAVY.AI vs. IBM Cloudant

System Properties Comparison Hazelcast vs. HEAVY.AI vs. IBM Cloudant

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Database as a Service offering based on Apache CouchDB

Primary database model

Key-value store

Relational DBMS

Document store

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Website

hazelcast.com

github.com/heavyai/heavydb
www.heavy.ai

www.ibm.com/products/cloudant

Technical documentation

hazelcast.org/imdg/docs

docs.heavy.ai

cloud.ibm.com/docs/Cloudant

Developer

Hazelcast

HEAVY.AI, Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2008

2016

2010

Current release

5.3.6, November 2023

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2; enterprise edition 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.

Implementation language

Java

C++ and CUDA

Erlang

Server operating systems

All OS with a Java VM

Linux

hosted

Data scheme

schema-free

yes

schema-free

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

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

RESTful HTTP/JSON API

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

View functions (Map-Reduce) in JavaScript

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

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More resources

Recent citations in the news

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7 March 2024, Forbes

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19 April 2023, Business Wire

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14 April 2023, InfoWorld

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
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