DBMS > 4D vs. Apache IoTDB vs. Firebird vs. OpenMLDB

System Properties Comparison 4D vs. Apache IoTDB vs. Firebird vs. OpenMLDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Firebird is an open source RDBMS forked from Borland's InterBase

An open-source machine learning database that provides a feature platform for training and inference

Primary database model

Secondary database models

Relational DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Website

Technical documentation

developer.4d.com

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

www.firebirdsql.org/en/reference-manuals

openmldb.ai/docs/zh/main

Developer

4D, Inc

Apache Software Foundation

Firebird Foundation

4 Paradigm Inc.

Initial release

1984

2018

2000

As fork of Borland's InterBase

2020

Current release

v20, April 2023

1.1.0, April 2023

5.0.0, January 2024

2024-2 February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Initial Developer's Public License

Open Source

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.

Implementation language

Java

C and C++

C++, Java, Scala

Server operating systems

OS X
Windows

All OS with a Java VM (>= 1.8)

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Data scheme

yes

Fixed schema

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

yes

close to SQL 92

SQL-like query language

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
Native API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
SQLAlchemy

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

yes

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

Users and groups

yes

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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