DBMS > FatDB vs. Firebase Realtime Database vs. Graphite vs. GridGain vs. MySQL

System Properties Comparison FatDB vs. Firebase Realtime Database vs. Graphite vs. GridGain vs. MySQL

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.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

GridGain is an in-memory computing platform, built on Apache Ignite

Widely used open source RDBMS

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/graphite-project/graphite-web

www.gridgain.com

www.mysql.com

Technical documentation

firebase.google.com/docs/database

graphite.readthedocs.io

www.gridgain.com/docs/index.html

dev.mysql.com/doc

Developer

FatCloud

Google

acquired by Google 2014

Chris Davis

GridGain Systems, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2006

2007

1995

Current release

GridGain 8.5.1

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Python

Java, C++, .Net

C and C++

Server operating systems

Windows

hosted

Linux
Unix

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

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

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
Sockets

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
JavaScript
Objective-C

JavaScript (Node.js)
Python

C#
C++
Java
PHP
Python
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

via applications

limited functionality with using 'rules'

yes (compute grid and cache interceptors can be used instead)

yes

proprietary syntax

Triggers

yes

via applications

Callbacks are triggered when data changes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes (replicated cache)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

Can implement custom security layer via applications

yes, based on authentication and database rules

Security Hooks for custom implementations

Users with fine-grained authorization concept

no user groups or roles

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