DBMS > IBM Cloudant vs. MySQL vs. Oracle NoSQL vs. PlanetScale

System Properties Comparison IBM Cloudant vs. MySQL vs. Oracle NoSQL vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Widely used open source RDBMS

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

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

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

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Website

www.ibm.com/products/cloudant

www.mysql.com

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

planetscale.com

Technical documentation

cloud.ibm.com/docs/Cloudant

dev.mysql.com/doc

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

planetscale.com/docs

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

PlanetScale

Initial release

2010

1995

2011

2020

Current release

8.4.0, April 2024

24.1, May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C and C++

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Docker
Linux
macOS

Data scheme

schema-free

yes

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

optional

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

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

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

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

Multi-source replication
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

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

not for MyISAM storage engine

Transaction concepts

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

atomic operations within a document possible

ACID

not for MyISAM storage engine

configurable

ACID within a storage node (=shard)

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

table locks or row locks depending on storage engine

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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