DBMS > Drizzle vs. Microsoft SQL Server vs. Oracle Rdb vs. Riak KV vs. SwayDB

System Properties Comparison Drizzle vs. Microsoft SQL Server vs. Oracle Rdb vs. Riak KV vs. SwayDB

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.

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.microsoft.com/en-us/sql-server

www.oracle.com/database/technologies/related/rdb.html

swaydb.simer.au

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

www.oracle.com/database/technologies/related/rdb-doc.html

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Drizzle project, originally started by Brian Aker

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

OpenSource, formerly Basho Technologies

Simer Plaha

Initial release

2008

1989

1984

2009

2018

Current release

7.2.4, September 2012

SQL Server 2022, November 2022

7.4.1.1, 2021

3.2.0, December 2022

License

Commercial or Open Source

Open Source

GNU GPL

commercial

restricted free version is available

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Erlang

Scala

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

HP Open VMS

Linux
OS X

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

Supported programming languages

C
C++
Java
PHP

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

Triggers

hooks for callbacks inside the server can be used.

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

selectable replication factor

none

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

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

yes, on a single node

Atomic execution of operations

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes, using Riak Security

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