DBMS > etcd vs. Microsoft SQL Server vs. OrientDB vs. Riak KV vs. Sadas Engine

System Properties Comparison etcd vs. Microsoft SQL Server vs. OrientDB vs. Riak KV vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

Distributed, fault tolerant key-value store

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

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

Key-value store

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

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

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

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

orientdb.org

www.sadasengine.com

Technical documentation

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

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

www.orientdb.com/docs/last/index.html

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

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

Developer

Microsoft

OrientDB LTD; CallidusCloud; SAP

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Initial release

1989

2010

2009

2006

Current release

3.4, August 2019

SQL Server 2022, November 2022

3.2.29, March 2024

3.2.0, December 2022

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache version 2

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

Erlang

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Linux
OS X

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

yes

APIs and other access methods

gRPC
JSON over HTTP

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

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

Server-side scripts

Stored procedures

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

Java, Javascript

Erlang

Triggers

yes, watching key changes

yes

Hooks

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, but depending on the SQL-Server Edition

Multi-source replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

links between data sets can be stored

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

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

yes, using Riak Security

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

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