DBMS > Hazelcast vs. Microsoft Azure Cosmos DB vs. openGemini vs. UniData,UniVerse

System Properties Comparison Hazelcast vs. Microsoft Azure Cosmos DB vs. openGemini vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Globally distributed, horizontally scalable, multi-model database service

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Multivalue DBMS

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	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

hazelcast.com

azure.microsoft.com/services/cosmos-db

www.opengemini.org
github.com/openGemini

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

hazelcast.org/imdg/docs

learn.microsoft.com/azure/cosmos-db

docs.opengemini.org/guide

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Hazelcast

Microsoft

Huawei and openGemini community

Rocket Software

Initial release

2008

2014

2022

1985

Current release

5.3.6, November 2023

1.1, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache Version 2.0

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

Server operating systems

All OS with a Java VM

hosted

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

Integer, Float, Boolean, String

optional

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

JavaScript

yes

Triggers

yes

Events

JavaScript

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

Implicit feature of the cloud service

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

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

Access rights can be defined down to the item level

Administrators and common users accounts

Access rights according to SQL-standard and operating system based

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