DBMS > FatDB vs. Hawkular Metrics vs. SQream DB vs. Titan

System Properties Comparison FatDB vs. Hawkular Metrics vs. SQream DB vs. Titan

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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.

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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

a GPU-based, columnar RDBMS for big data analytics workloads

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Graph DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

www.hawkular.org

sqream.com

github.com/thinkaurelius/titan

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.sqream.com

github.com/thinkaurelius/titan/wiki

Developer

FatCloud

Community supported by Red Hat

SQream Technologies

Aurelius, owned by DataStax

Initial release

2012

2014

2017

2012

Current release

2022.1.6, December 2022

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

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

Windows

Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

APIs and other access methods

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

HTTP REST

.Net
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Go
Java
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

via applications

user defined functions in Python

yes

Triggers

yes

via applications

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal and vertical partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

ACID

Concurrency

Support for concurrent manipulation of data

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

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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