DBMS > Blueflood vs. Drizzle vs. Sadas Engine

System Properties Comparison Blueflood vs. Drizzle vs. Sadas Engine

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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

Scalable TimeSeries DBMS based on Cassandra

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

blueflood.io

www.sadasengine.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Rackspace

Drizzle project, originally started by Brian Aker

SADAS s.r.l.

Initial release

2013

2008

2006

Current release

7.2.4, September 2012

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X

FreeBSD
Linux
OS X

AIX
Linux
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

HTTP REST

JDBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C++
Java
PHP

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

managed by 'Learn by Usage'

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles according to SQL-standard

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