DBMS > Amazon Redshift vs. Firebolt vs. Prometheus vs. TimescaleDB

System Properties Comparison Amazon Redshift vs. Firebolt vs. Prometheus vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Open-source Time Series DBMS and monitoring system

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

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.49
Rank	#148	Overall
	#68	Relational DBMS

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

aws.amazon.com/redshift

www.firebolt.io

prometheus.io

www.timescale.com

Technical documentation

docs.aws.amazon.com/redshift

docs.firebolt.io

prometheus.io/docs

docs.timescale.com

Developer

Amazon (based on PostgreSQL)

Firebolt Analytics Inc.

Timescale

Initial release

2012

2020

2015

2017

Current release

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Server operating systems

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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.

Import of XML data 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

.Net
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

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

Supported programming languages

All languages supporting JDBC/ODBC

Go
JavaScript (Node.js)
Python

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
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

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

yes

by Federation

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

none

Immediate 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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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