DBMS > EventStoreDB vs. FatDB vs. JaguarDB

System Properties Comparison EventStoreDB vs. FatDB vs. JaguarDB

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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

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

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

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Event Store

Document store
Key-value store

Key-value store
Vector DBMS

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

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Website

www.eventstore.com

www.jaguardb.com

Technical documentation

developers.eventstore.com

www.jaguardb.com/support.html

Developer

Event Store Limited

FatCloud

DataJaguar, Inc.

Initial release

2012

2015

Current release

21.2, February 2021

3.3 July 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

GPL V3.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

the server part. Clients available in other languages

Server operating systems

Linux
Windows

Windows

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

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

JDBC
ODBC

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Can implement custom security layer via applications

rights management via user accounts

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