DBMS > 4D vs. Apache IoTDB vs. eXtremeDB vs. H2 vs. RDFox

System Properties Comparison 4D vs. Apache IoTDB vs. eXtremeDB vs. H2 vs. RDFox

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

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	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

www.oxfordsemantic.tech

Technical documentation

developer.4d.com

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

www.mcobject.com/docs/extremedb.htm

www.h2database.com/html/main.html

docs.oxfordsemantic.tech

Developer

4D, Inc

Apache Software Foundation

McObject

Thomas Mueller

Oxford Semantic Technologies

Initial release

1984

2018

2001

2005

2017

Current release

v20, April 2023

1.1.0, April 2023

8.2, 2021

2.2.220, July 2023

6.0, Septermber 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

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++

Java

C++

Server operating systems

OS X
Windows

All OS with a Java VM (>= 1.8)

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux
macOS
Windows

Data scheme

yes

RDF schemas

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language

yes

with the option: eXtremeSQL

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
Native API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JDBC
ODBC

RESTful HTTP API
SPARQL 1.1

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Go
Java
Python
Scala

.Net
C
C#
C++
Java
Lua
Python
Scala

Java

C
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

horizontal partitioning / sharding

none

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

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

With clustering: 2 database servers on different computers operate on identical copies of a database

replication via a shared file system

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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

Optimistic (MVCC) and pessimistic (locking) strategies available

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Roles, resources, and access types

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

AMD EPYC 4364P & 4564P @ DDR5-4800 / DDR5-5200 vs. Intel Xeon E-2488 Review
6 June 2024, Phoronix

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

Linux 6.5 With AMD P-State EPP Default Brings Performance & Power Efficiency Benefits For Ryzen Servers
21 September 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review
10 October 2023, Phoronix

provided by Google News

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

McObject Delivers eXtremeDB 8.4 Improving Performance, Security, and Developer Productivity
13 May 2024, Embedded Computing Design

McObject LLC Joins STMicroelectronics Partner Program to Expand, Enhance and Accelerate Customer
6 June 2024, EIN News

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject’s new eXtremeDB Cluster provides distributed database solution for real-time apps
20 July 2011, Embedded

provided by Google News

Use semantic reasoning to infer new facts from your RDF graph by integrating RDFox with Amazon Neptune | Amazon ...
20 February 2023, AWS Blog

The intuitions behind Knowledge Graphs and Reasoning | by Peter Crocker
5 May 2020, Towards Data Science

Eight interesting open-source graph databases
3 January 2023, INDIAai

Financial Crime Discovery using Amazon EKS and Graph Databases | Amazon Web Services
1 February 2022, AWS Blog

Top 9 Open Source Graph Databases
7 November 2022, Analytics India Magazine

provided by Google News

Share this page