DBMS > Amazon Redshift vs. EJDB vs. Hawkular Metrics vs. RRDtool vs. TimescaleDB

System Properties Comparison Amazon Redshift vs. EJDB vs. Hawkular Metrics vs. RRDtool vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/redshift

github.com/Softmotions/ejdb

www.hawkular.org

oss.oetiker.ch/rrdtool

www.timescale.com

Technical documentation

docs.aws.amazon.com/redshift

github.com/Softmotions/ejdb/blob/master/README.md

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

oss.oetiker.ch/rrdtool/doc

docs.timescale.com

Developer

Amazon (based on PostgreSQL)

Softmotions

Community supported by Red Hat

Tobias Oetiker

Timescale

Initial release

2012

2014

1999

2017

Current release

1.8.0, 2022

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

Open Source

Apache 2.0

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

Server operating systems

hosted

server-less

Linux
OS X
Windows

HP-UX
Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Numeric data only

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC

in-process shared library

HTTP REST

in-process shared library
Pipes

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

Supported programming languages

All languages supporting JDBC/ODBC

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on Cassandra

none

Source-replica replication with hot standby and reads on replicas

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

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