DBMS > Amazon DocumentDB vs. Hazelcast vs. MySQL vs. Oracle Coherence vs. UniData,UniVerse

System Properties Comparison Amazon DocumentDB vs. Hazelcast vs. MySQL vs. Oracle Coherence vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

A widely adopted in-memory data grid

Widely used open source RDBMS

Oracles in-memory data grid solution

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

Primary database model

Document store

Key-value store

Relational DBMS

Key/Value like access via memcached API

Key-value store

Multivalue DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	1.89
Rank	#137	Overall
	#24	Document stores

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Score	3.47
Rank	#93	Overall
	#2	Multivalue DBMS

Website

aws.amazon.com/documentdb

hazelcast.com

www.mysql.com

www.oracle.com/java/coherence

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

Technical documentation

aws.amazon.com/documentdb/resources

hazelcast.org/imdg/docs

dev.mysql.com/doc

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

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

Developer

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Rocket Software

Initial release

2019

2008

1995

2007

1985

Current release

5.3.6, November 2023

8.3.0, January 2024

14.1, August 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Java

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JCache
JPA
RESTful HTTP API

Java API

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

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Java

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

proprietary syntax

yes

Triggers

yes

Events

yes

Live Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Replicated Map

Multi-source replication
Source-replica replication

yes, with selectable consistency level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-document operations

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

ACID

not for MyISAM storage engine

configurable

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Access rights for users and roles

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

authentification to access the cache via certificates or http basic authentication

Access rights according to SQL-standard and operating system based

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