DBMS > EJDB vs. Hazelcast vs. Oracle NoSQL vs. STSdb

System Properties Comparison EJDB vs. Hazelcast vs. Oracle NoSQL vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A widely adopted in-memory data grid

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store

Key-value store

Document store
Key-value store
Relational DBMS

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/Softmotions/ejdb

hazelcast.com

www.oracle.com/database/nosql/technologies/nosql

github.com/STSSoft/STSdb4

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

hazelcast.org/imdg/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Softmotions

Hazelcast

Oracle

STS Soft SC

Initial release

2012

2008

2011

Current release

5.3.6, November 2023

23.3, December 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2; commercial licenses available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPLv2, commercial license available

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.

Implementation language

Java

Server operating systems

server-less

All OS with a Java VM

Linux
Solaris SPARC/x86

Windows

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

optional

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

APIs and other access methods

in-process shared library

JCache
JPA
Memcached protocol
RESTful HTTP API

RESTful HTTP API

.NET Client API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

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

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

off heap cache

User concepts

Access control

Role-based access control

Access rights for users and roles

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