DBMS > FatDB vs. Heroic vs. mSQL vs. ReductStore

System Properties Comparison FatDB vs. Heroic vs. mSQL vs. ReductStore

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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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

mSQL (Mini SQL) is a simple and lightweight RDBMS

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

github.com/spotify/heroic

hughestech.com.au/products/msql

github.com/reductstore
www.reduct.store

Technical documentation

spotify.github.io/heroic

www.reduct.store/docs

Developer

FatCloud

Spotify

Hughes Technologies

ReductStore LLC

Initial release

2012

2014

1994

2023

Current release

4.4, October 2021

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

Business Source License 1.1

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

C++, Rust

Server operating systems

Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS
Windows

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

via Elasticsearch

yes

SQL

Support of SQL

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC

HTTP API

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

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

none

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

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