DBMS > IBM Cloudant vs. MySQL vs. OpenEdge vs. Spark SQL vs. TimescaleDB

System Properties Comparison IBM Cloudant vs. MySQL vs. OpenEdge vs. Spark SQL vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Widely used open source RDBMS

Application development environment with integrated database management system

Spark SQL is a component on top of 'Spark Core' for structured data processing

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational 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	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

www.ibm.com/products/cloudant

www.mysql.com

www.progress.com/openedge

spark.apache.org/sql

www.timescale.com

Technical documentation

cloud.ibm.com/docs/Cloudant

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

spark.apache.org/docs/latest/sql-programming-guide.html

docs.timescale.com

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Apache Software Foundation

Timescale

Initial release

2010

1995

1984

2014

2017

Current release

8.4.0, April 2024

OpenEdge 12.2, March 2020

3.5.0 ( 2.13), September 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

C and C++

Scala

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

close to SQL 92

SQL-like DML and DDL statements

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

Progress proprietary ABL (Advanced Business Language)

Java
Python
R
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

since Version 11.4

yes, utilizing Spark Core

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

Users and groups

fine grained access rights according to SQL-standard

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