DBMS > FatDB vs. Firebase Realtime Database vs. Graphite vs. Snowflake vs. Titan

System Properties Comparison FatDB vs. Firebase Realtime Database vs. Graphite vs. Snowflake vs. Titan

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.

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

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

Cloud-based data warehousing service for structured and semi-structured data

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Key-value store

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/graphite-project/graphite-web

www.snowflake.com

github.com/thinkaurelius/titan

Technical documentation

firebase.google.com/docs/database

graphite.readthedocs.io

docs.snowflake.net/manuals/index.html

github.com/thinkaurelius/titan/wiki

Developer

FatCloud

Google

acquired by Google 2014

Chris Davis

Snowflake Computing Inc.

Aurelius, owned by DataStax

Initial release

2012

2006

2014

2012

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Python

Java

Server operating systems

Windows

hosted

Linux
Unix

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

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

CLI Client
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Java
JavaScript
Objective-C

JavaScript (Node.js)
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

via applications

limited functionality with using 'rules'

user defined functions

yes

Triggers

yes

via applications

Callbacks are triggered when data changes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

yes, based on authentication and database rules

Users with fine-grained authorization concept, user roles and pluggable authentication

User authentification and security via Rexster Graph Server

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