DBMS > 4D vs. Blueflood vs. Drizzle

System Properties Comparison 4D vs. Blueflood vs. Drizzle

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Application development environment with integrated database management system

Scalable TimeSeries DBMS based on Cassandra

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Website

www.4d.com

blueflood.io

Technical documentation

developer.4d.com

github.com/rax-maas/blueflood/wiki

Developer

4D, Inc

Rackspace

Drizzle project, originally started by Brian Aker

Initial release

1984

2013

2008

Current release

v20, April 2023

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU GPL

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C++

Server operating systems

OS X
Windows

Linux
OS X

FreeBSD
Linux
OS X

Data scheme

yes

predefined 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

yes

close to SQL 92

yes

with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP REST

JDBC

Supported programming languages

4D proprietary IDE
PHP

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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.

User concepts

Access control

Users and groups

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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More resources

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