DBMS > EJDB vs. IBM Cloudant vs. Newts vs. Oracle NoSQL vs. OrigoDB

System Properties Comparison EJDB vs. IBM Cloudant vs. Newts vs. Oracle NoSQL vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering based on Apache CouchDB

Time Series DBMS based on Cassandra

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

A fully ACID in-memory object graph database

Primary database model

Document store

Time Series DBMS

Document store
Key-value store
Relational DBMS

Document store
Object oriented DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

github.com/Softmotions/ejdb

www.ibm.com/products/cloudant

opennms.github.io/newts

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

origodb.com

Technical documentation

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

cloud.ibm.com/docs/Cloudant

github.com/OpenNMS/newts/wiki

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

origodb.com/docs

Developer

Softmotions

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

OpenNMS Group

Oracle

Robert Friberg et al

Initial release

2012

2010

2014

2011

2009

under the name LiveDB

Current release

23.3, December 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache 2.0

Open Source

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

Open Source

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

Erlang

Java

Server operating systems

server-less

hosted

Linux
OS X
Windows

Linux
Solaris SPARC/x86

Linux
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

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

in-process shared library

RESTful HTTP/JSON API

HTTP REST
Java API

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java

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

.Net

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

depending on model

Transaction concepts

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

atomic operations within a document possible

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles

Role based authorization

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