DBMS > Datomic vs. FatDB vs. Oracle Berkeley DB vs. Valentina Server vs. Yaacomo

System Properties Comparison Datomic vs. FatDB vs. Oracle Berkeley DB vs. Valentina Server 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

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

Widely used in-process key-value store

Object-relational database and reports server

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

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.datomic.com

www.oracle.com/database/technologies/related/berkeleydb.html

www.valentina-db.net

yaacomo.com

Technical documentation

docs.datomic.com

docs.oracle.com/cd/E17076_05/html/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Cognitect

FatCloud

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Paradigma Software

Q2WEB GmbH

Initial release

2012

1994

1999

2009

Current release

1.0.6735, June 2023

18.1.40, May 2020

5.7.5

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

commercial license available

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

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

All OS with a Java VM

Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Windows

Android
Linux
Windows

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

RESTful HTTP API

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

ODBC

JDBC
ODBC

Supported programming languages

Clojure
Java

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

via applications

yes

Triggers

By using transaction functions

yes

via applications

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor

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

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

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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