DBMS > Datomic vs. OushuDB

System Properties Comparison Datomic vs. OushuDB

Please select another system to include it in the comparison.

Our visitors often compare Datomic and OushuDB with Google BigQuery.

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

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

Primary database model

Relational DBMS

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

Score	1.57
Rank	#146	Overall
	#66	Relational DBMS

Score	0.01
Rank	#368	Overall
	#154	Relational DBMS

Website

www.datomic.com

www.oushu.com/product/oushuDB

Technical documentation

docs.datomic.com

www.oushu.com/documentation

Developer

Cognitect

Oushu

Initial release

2012

Current release

1.0.7075, December 2023

4.0.1, August 2020

License

Commercial or Open Source

commercial

limited edition free

commercial

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

Java, Clojure

Server operating systems

All OS with a Java VM

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Full-featured ANSI SQL support

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Clojure
Java

C
C++

Server-side scripts

Stored procedures

yes

Transaction Functions

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

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

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

User concepts

Access control

Kerberos, SSL and role based access

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Nubank buys firm behind Clojure programming language
28 July 2020, Finextra

Brazil’s Nubank acquires US software firm Cognitect, creator of Clojure and Datomic
24 July 2020, LatamList

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Lucas Cavalcanti on Using Clojure, Microservices, Hexagonal Architecture and Public Cloud at Nubank
16 August 2021, InfoQ.com

Zoona Case Study
16 December 2017, AWS Blog

provided by Google News

China's answer to Snowflake is shaping as data demands upgrade
8 September 2021, PingWest

provided by Google News

Share this page