DBMS > Datomic vs. Memcached vs. Microsoft SQL Server vs. OushuDB

System Properties Comparison Datomic vs. Memcached vs. Microsoft SQL Server vs. OushuDB

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

In-memory key-value store, originally intended for caching

Microsofts flagship relational DBMS

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	16.84
Rank	#32	Overall
	#4	Key-value stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

www.datomic.com

www.memcached.org

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

www.oushu.com/product/oushuDB

Technical documentation

docs.datomic.com

github.com/memcached/memcached/wiki

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

www.oushu.com/documentation

Developer

Cognitect

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Oushu

Initial release

2012

2003

1989

Current release

1.0.7180, July 2024

1.6.29, June 2024

SQL Server 2022, November 2022

4.0.1, August 2020

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD license

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Linux

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

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

RESTful HTTP API

Proprietary protocol

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

JDBC
ODBC

Supported programming languages

Clojure
Java

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

C
C++

Server-side scripts

Stored procedures

yes

Transaction Functions

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

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Repcached, a Memcached patch, provides this functionallity

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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