DBMS > Apache IoTDB vs. dBASE vs. MySQL vs. OpenEdge vs. Trafodion

System Properties Comparison Apache IoTDB vs. dBASE vs. MySQL vs. OpenEdge vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

Widely used open source RDBMS

Application development environment with integrated database management system

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

iotdb.apache.org

www.dbase.com

www.mysql.com

www.progress.com/openedge

trafodion.apache.org

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.dbase.com/support/knowledgebase

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Asthon Tate

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Apache Software Foundation, originally developed by HP

Initial release

2018

1979

1995

1984

2014

Current release

1.1.0, April 2023

dBASE 2019, 2019

8.4.0, April 2024

OpenEdge 12.2, March 2020

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++, Java

Server operating systems

All OS with a Java VM (>= 1.8)

DOS

dBase Classic
Windows

dBase Pro

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

close to SQL 92

yes

APIs and other access methods

JDBC
Native API

none

The IDE can access other DBMS or ODBC-sources.

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

dBase proprietary IDE

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)

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

The IDE can access stored procedures in other database systems.

yes

proprietary syntax

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

Multi-source replication
Source-replica replication

Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

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

In-memory capabilities

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

yes

User concepts

Access control

yes

Access rights for users and roles

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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