DBMS > Amazon Redshift vs. Hawkular Metrics vs. RRDtool vs. SAP SQL Anywhere vs. Sequoiadb

System Properties Comparison Amazon Redshift vs. Hawkular Metrics vs. RRDtool vs. SAP SQL Anywhere vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

aws.amazon.com/redshift

www.hawkular.org

oss.oetiker.ch/rrdtool

www.sap.com/products/technology-platform/sql-anywhere.html

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/redshift

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

oss.oetiker.ch/rrdtool/doc

help.sap.com/docs/SAP_SQL_Anywhere

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon (based on PostgreSQL)

Community supported by Red Hat

Tobias Oetiker

SAP

formerly Sybase

Sequoiadb Ltd.

Initial release

2012

2014

1999

1992

2013

Current release

1.8.0, 2022

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

commercial

Open Source

Server: AGPL; Client: Apache V2

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

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

hosted

Linux
OS X
Windows

HP-UX
Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

oid, date, timestamp, binary, regex

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.

Exporting into and restoring from XML files possible

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

HTTP REST

in-process shared library
Pipes

ADO.NET
HTTP API
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in C/C++, Java, .Net or Perl

JavaScript

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

none

Source-replica replication

Database mirroring

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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