DBMS > IBM Cloudant vs. IBM Db2 Event Store vs. Newts vs. Oracle NoSQL

System Properties Comparison IBM Cloudant vs. IBM Db2 Event Store vs. Newts vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Distributed Event Store optimized for Internet of Things use cases

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

Primary database model

Document store

Event Store
Time Series DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

www.ibm.com/products/cloudant

www.ibm.com/products/db2-event-store

opennms.github.io/newts

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

Technical documentation

cloud.ibm.com/docs/Cloudant

www.ibm.com/docs/en/db2-event-store

github.com/OpenNMS/newts/wiki

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

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

IBM

OpenNMS Group

Oracle

Initial release

2010

2017

2014

2011

Current release

2.0

24.1, May 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

Open Source

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

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

C and C++

Java

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Linux
Solaris SPARC/x86

Data scheme

schema-free

yes

schema-free

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

RESTful HTTP API

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Java

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

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Active-active shard replication

selectable replication factor

based on Cassandra

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

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

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)

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights for users and roles

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