DBMS > Hawkular Metrics vs. Hypertable vs. OushuDB vs. Sadas Engine

System Properties Comparison Hawkular Metrics vs. Hypertable vs. OushuDB vs. Sadas Engine

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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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Time Series DBMS

Wide column store

Relational DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

www.hawkular.org

www.oushu.com/product/oushuDB

www.sadasengine.com

Technical documentation

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

www.oushu.com/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Community supported by Red Hat

Hypertable Inc.

Oushu

SADAS s.r.l.

Initial release

2014

2009

2006

Current release

0.9.8.11, March 2016

4.0.1, August 2020

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

commercial

free trial version available

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++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux

AIX
Linux
Windows

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.

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

Full-featured ANSI SQL support

yes

APIs and other access methods

HTTP REST

C++ API
Thrift

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

Go
Java
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C
C++

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

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.

yes

managed by 'Learn by Usage'

User concepts

Access control

Kerberos, SSL and role based access

Access rights for users, groups and roles according to SQL-standard

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