DBMS > Datomic vs. EventStoreDB vs. FoundationDB

System Properties Comparison Datomic vs. EventStoreDB vs. FoundationDB

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Ordered key-value store. Core features are complimented by layers.

Primary database model

Relational DBMS

Event Store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Website

www.datomic.com

www.eventstore.com

github.com/apple/foundationdb

Technical documentation

docs.datomic.com

developers.eventstore.com

apple.github.io/foundationdb

Developer

Cognitect

Event Store Limited

FoundationDB

Initial release

2012

2013

Current release

1.0.6735, June 2023

21.2, February 2021

6.2.28, November 2020

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Server operating systems

All OS with a Java VM

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

some layers support schemas

Typing

predefined data types such as float or date

yes

some layers support typing

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

supported in specific SQL layer only

APIs and other access methods

RESTful HTTP API

Supported programming languages

Clojure
Java

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Server-side scripts

Stored procedures

yes

Transaction Functions

in SQL-layer only

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Foreign keys

Referential integrity

in SQL-layer only

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

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