DBMS > Datomic vs. FatDB vs. Snowflake

System Properties Comparison Datomic vs. FatDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

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

Description

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

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

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

Score	2.29
Rank	#140	Overall
	#66	Relational DBMS

Score	120.89
Rank	#11	Overall
	#8	Relational DBMS

Website

www.datomic.com

www.snowflake.com

Technical documentation

docs.datomic.com

docs.snowflake.net/manuals/index.html

Developer

Cognitect

FatCloud

Snowflake Computing Inc.

Initial release

2012

2014

Current release

1.0.6735, June 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java, Clojure

Server operating systems

All OS with a Java VM

Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Via inetgration in SQL Server

yes

APIs and other access methods

RESTful HTTP API

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

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
Java

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

via applications

user defined functions

Triggers

By using transaction functions

yes

via applications

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor

yes

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

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

Can implement custom security layer via applications

Users with fine-grained authorization concept, user roles and pluggable authentication

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