DBMS > Hawkular Metrics vs. Hypertable vs. Microsoft Azure SQL Database vs. Postgres-XL

System Properties Comparison Hawkular Metrics vs. Hypertable vs. Microsoft Azure SQL Database vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Primary database model

Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

www.hawkular.org

azure.microsoft.com/en-us/products/azure-sql/database

www.postgres-xl.org

Technical documentation

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

docs.microsoft.com/en-us/azure/azure-sql

www.postgres-xl.org/documentation

Developer

Community supported by Red Hat

Hypertable Inc.

Microsoft

Initial release

2014

2009

2010

2014

since 2012, originally named StormDB

Current release

0.9.8.11, March 2016

V12

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Mozilla public license

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

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Linux
macOS

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

HTTP REST

C++ API
Thrift

ADO.NET
JDBC
ODBC

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

Supported programming languages

Go
Java
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

Transact SQL

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor on file system level

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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