DBMS > Hawkular Metrics vs. Prometheus vs. SpaceTime vs. SQLite vs. Trino

System Properties Comparison Hawkular Metrics vs. Prometheus vs. SpaceTime vs. SQLite vs. Trino

Editorial information provided by DB-Engines

Name

Description

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

Open-source Time Series DBMS and monitoring system

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Widely used embeddable, in-process RDBMS

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Time Series DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

www.hawkular.org

prometheus.io

www.mireo.com/spacetime

www.sqlite.org

trino.io

Technical documentation

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

prometheus.io/docs

www.sqlite.org/docs.html

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Community supported by Red Hat

Mireo

Dwayne Richard Hipp

Trino Software Foundation

Initial release

2014

2015

2020

2000

2012

2020 rebranded from PrestoSQL

Current release

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

Public Domain

Open Source

Apache Version 2.0

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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux

server-less

Linux
macOS

for devlopment

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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.

Import of XML data possible

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

A subset of ANSI SQL is implemented

yes

SQL-92 is not fully supported

yes

APIs and other access methods

HTTP REST

RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Go
Java
Python
Ruby

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

C#
C++
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes, depending on connected data-source

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Fixed-grid hypercubes

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

by Federation

Real-time block device replication (DRBD)

none

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

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

yes

User concepts

Access control

yes

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

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Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

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News

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22 May 2024

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8 May 2024

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24 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.