DBMS > 4D vs. FeatureBase vs. jBASE vs. RRDtool

System Properties Comparison 4D vs. FeatureBase vs. jBASE vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

A robust multi-value DBMS comprising development tools and middleware

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Relational DBMS

Multivalue DBMS

Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

www.4d.com

www.featurebase.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

oss.oetiker.ch/rrdtool

Technical documentation

developer.4d.com

docs.featurebase.com

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

oss.oetiker.ch/rrdtool/doc

Developer

4D, Inc

Molecula and Pilosa Open Source Contributors

Rocket Software (formerly Zumasys)

Tobias Oetiker

Initial release

1984

2017

1991

1999

Current release

v20, April 2023

2022, May 2022

5.7

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

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

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

OS X
Windows

Linux
macOS

AIX
Linux
Windows

HP-UX
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL queries

Embedded SQL for jBASE in BASIC

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

in-process shared library
Pipes

Supported programming languages

4D proprietary IDE
PHP

Java
Python

.Net
Basic
Jabbascript
Java

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

Access rights can be defined down to the item level

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More resources

DB-Engines blog posts

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

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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