DBMS > Fauna vs. MySQL vs. Quasardb vs. Titan vs. Trafodion

System Properties Comparison Fauna vs. MySQL vs. Quasardb vs. Titan vs. Trafodion

Editorial information provided by DB-Engines

Name

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.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Widely used open source RDBMS

Distributed, high-performance timeseries database

Titan is a Graph DBMS optimized for distributed clusters.

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

fauna.com

www.mysql.com

quasar.ai

github.com/thinkaurelius/titan

trafodion.apache.org

Technical documentation

docs.fauna.com

dev.mysql.com/doc

doc.quasar.ai/master

github.com/thinkaurelius/titan/wiki

trafodion.apache.org/documentation.html

Developer

Fauna, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

Aurelius, owned by DataStax

Apache Software Foundation, originally developed by HP

Initial release

2014

1995

2009

2012

2014

Current release

8.4.0, April 2024

3.14.1, January 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache license, version 2.0

Open Source

Apache 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.

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Implementation language

Scala

C and C++

C++

Java

C++, Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Clojure
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via Faunus, a graph analytics engine

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Relationships in graph

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

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

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Identity management, authentication, and access control

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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