DBMS > Apache Drill vs. DataFS vs. Hawkular Metrics vs. Microsoft Azure Table Storage

System Properties Comparison Apache Drill vs. DataFS vs. Hawkular Metrics vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

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

Primary database model

Document store
Relational DBMS

Object oriented DBMS

Time Series DBMS

Wide column store

Secondary database models

Graph DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

drill.apache.org

newdatabase.com

www.hawkular.org

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

Technical documentation

drill.apache.org/docs

dev.mobiland.com/Overview.xsp

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

Developer

Apache Software Foundation

Mobiland AG

Community supported by Red Hat

Microsoft

Initial release

2012

2018

2014

2012

Current release

1.20.3, January 2023

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

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

Java

Server operating systems

Linux
OS X
Windows

Windows

Linux
OS X
Windows

hosted

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

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.

Secondary indexes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

HTTP REST

RESTful HTTP API

Supported programming languages

C++

.Net
C
C#
C++
VB.Net

Go
Java
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

Triggers

no, except callback-events from server when changes happened

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

Windows-Profile

Access rights based on private key authentication or shared access signatures

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More resources

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