DBMS > Drizzle vs. EDB Postgres vs. etcd vs. FatDB vs. MySQL

System Properties Comparison Drizzle vs. EDB Postgres vs. etcd vs. FatDB vs. MySQL

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.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

A distributed reliable key-value store

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Widely used open source RDBMS

Primary database model

Relational DBMS

Key-value store

Document store
Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.enterprisedb.com

etcd.io
github.com/etcd-io/etcd

www.mysql.com

Technical documentation

www.enterprisedb.com/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

dev.mysql.com/doc

Developer

Drizzle project, originally started by Brian Aker

EnterpriseDB

FatCloud

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2008

2005

2012

1995

Current release

7.2.4, September 2012

14, December 2021

3.4, August 2019

8.4.0, April 2024

License

Commercial or Open Source

Open Source

GNU GPL

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

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Implementation language

C++

C and C++

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

FreeBSD
Linux
Windows

experimental

Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

standard with numerous extensions

Via inetgration in SQL Server

yes

with proprietary extensions

APIs and other access methods

JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

gRPC
JSON over HTTP

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Java
PHP

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

via applications

yes

proprietary syntax

Triggers

hooks for callbacks inside the server can be used.

yes

yes, watching key changes

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

Users with fine-grained authorization concept

no user groups or roles

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