DBMS > MySQL vs. OpenEdge vs. PouchDB vs. Spark SQL vs. TDengine

System Properties Comparison MySQL vs. OpenEdge vs. PouchDB vs. Spark SQL vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

Application development environment with integrated database management system

JavaScript DBMS with an API inspired by CouchDB

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

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

www.mysql.com

www.progress.com/openedge

pouchdb.com

spark.apache.org/sql

github.com/taosdata/TDengine
tdengine.com

Technical documentation

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

pouchdb.com/guides

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

docs.tdengine.com

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Apache Software Foundation

TDEngine, previously Taos Data

Initial release

1995

1984

2012

2014

2019

Current release

8.3.0, January 2024

OpenEdge 12.2, March 2020

7.1.1, June 2019

3.5.0 ( 2.13), September 2023

3.0, August 2022

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Open Source

AGPL V3, also commercial editions 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

JavaScript

Scala

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

via views

SQL

Support of SQL

yes

with proprietary extensions

yes

close to SQL 92

SQL-like DML and DDL statements

Standard SQL with extensions for time-series applications

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

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)

JavaScript

Java
Python
R
Scala

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

View functions in JavaScript

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

since Version 11.4

Sharding

with a proxy-based framework, named couchdb-lounge

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Users with fine-grained authorization concept

no user groups or roles

Users and groups

yes

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Market metrics

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Licensing and pricing models

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