DBMS > Microsoft Azure Table Storage vs. Postgres-XL vs. Titan vs. Trafodion

System Properties Comparison Microsoft Azure Table Storage vs. Postgres-XL vs. Titan vs. Trafodion

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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

A Wide Column Store for rapid development using massive semi-structured datasets

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Titan is a Graph DBMS optimized for distributed clusters.

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

azure.microsoft.com/en-us/services/storage/tables

www.postgres-xl.org

github.com/thinkaurelius/titan

trafodion.apache.org

Technical documentation

www.postgres-xl.org/documentation

github.com/thinkaurelius/titan/wiki

trafodion.apache.org/documentation.html

Developer

Microsoft

Aurelius, owned by DataStax

Apache Software Foundation, originally developed by HP

Initial release

2012

2014

since 2012, originally named StormDB

2012

2014

Current release

10 R1, October 2018

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

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

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Implementation language

Java

C++, Java

Server operating systems

hosted

Linux
macOS

Linux
OS X
Unix
Windows

Linux

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC

Supported programming languages

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Clojure
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Relationships in graph

yes

Transaction concepts

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

optimistic locking

ACID

MVCC

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

yes

In-memory capabilities

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

User concepts

Access control

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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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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Recent citations in the news

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
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How to use Azure Table storage in .Net
14 January 2019, InfoWorld

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7 October 2015, Microsoft

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

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20 August 2015, All Things Distributed

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24 August 2015, AWS Blog

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13 January 2017, Datanami

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14 November 2019, InfoWorld

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