DBMS > Datomic vs. EJDB vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison Datomic vs. EJDB vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

A Wide Column Store for rapid development using massive semi-structured datasets

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Document store

Document store
Key-value store

Wide column store

Relational DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

www.datomic.com

github.com/Softmotions/ejdb

azure.microsoft.com/en-us/services/storage/tables

yaacomo.com

Technical documentation

docs.datomic.com

github.com/Softmotions/ejdb/blob/master/README.md

Developer

Cognitect

Softmotions

FatCloud

Microsoft

Q2WEB GmbH

Initial release

2012

2009

Current release

1.0.7075, December 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPLv2

commercial

Cloud-based only

Only available as a cloud service

yes

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

server-less

Windows

hosted

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

Via inetgration in SQL Server

yes

APIs and other access methods

RESTful HTTP API

in-process shared library

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Clojure
Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

via applications

Triggers

By using transaction functions

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Can implement custom security layer via applications

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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