DBMS > Drizzle vs. Heroic vs. mSQL vs. SWC-DB

System Properties Comparison Drizzle vs. Heroic vs. mSQL vs. SWC-DB

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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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

mSQL (Mini SQL) is a simple and lightweight RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

github.com/spotify/heroic

hughestech.com.au/products/msql

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

spotify.github.io/heroic

Developer

Drizzle project, originally started by Brian Aker

Spotify

Hughes Technologies

Alex Kashirin

Initial release

2008

2014

1994

2020

Current release

7.2.4, September 2012

4.4, October 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

GPL V3

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++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

yes

with proprietary extensions

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

C
C++
Java
PHP

C
C++
Delphi
Java
Perl
PHP
Tcl

C++

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

none

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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More resources

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