DBMS > 4D vs. OpenQM vs. RocksDB vs. RRDtool vs. Solr

System Properties Comparison 4D vs. OpenQM vs. RocksDB vs. RRDtool vs. Solr

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

QpenQM is a high-performance, self-tuning, multi-value DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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.

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.4d.com

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

rocksdb.org

oss.oetiker.ch/rrdtool

solr.apache.org

Technical documentation

developer.4d.com

github.com/facebook/rocksdb/wiki

oss.oetiker.ch/rrdtool/doc

solr.apache.org/resources.html

Developer

4D, Inc

Rocket Software, originally Martin Phillips

Facebook, Inc.

Tobias Oetiker

Apache Software Foundation

Initial release

1984

1993

2013

1999

2006

Current release

v20, April 2023

3.4-12

9.2.1, May 2024

1.8.0, 2022

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

BSD

Open Source

GPL V2 and FLOSS

Open Source

Apache Version 2

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

C++

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

Java

Server operating systems

OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

HP-UX
Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

with some exceptions

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

Numeric data only

yes

supports customizable data types and automatic typing

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

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

close to SQL 92

Solr Parallel SQL Interface

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

C++ API
Java API

in-process shared library
Pipes

Java API
RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

.Net
Basic
C
Java
Objective C
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Access rights can be defined down to the item level

yes

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