DBMS > Hawkular Metrics vs. PostGIS vs. Sequoiadb vs. SQLite vs. TimescaleDB

System Properties Comparison Hawkular Metrics vs. PostGIS vs. Sequoiadb vs. SQLite vs. TimescaleDB

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.

Spatial extension of PostgreSQL

NewSQL database with distributed OLTP and SQL

Widely used embeddable, in-process RDBMS

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

Primary database model

Time Series DBMS

Spatial DBMS

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

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

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

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

postgis.net/documentation

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

www.sqlite.org/docs.html

docs.timescale.com

Developer

Community supported by Red Hat

Sequoiadb Ltd.

Dwayne Richard Hipp

Timescale

Initial release

2014

2005

2013

2000

2017

Current release

3.4.2, February 2024

3.45.3 (15 April 2024), April 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL v2.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

Public Domain

Open Source

Apache 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.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

Linux

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes

not rigid because of 'dynamic typing' concept.

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP REST

proprietary protocol using JSON

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Supported programming languages

Go
Java
Python
Ruby

.Net
C++
Java
PHP
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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

JavaScript

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

based on Cassandra

yes

based on PostgreSQL

Sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

based on PostgreSQL

Source-replica replication

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

based on PostgreSQL

simple password-based access control

fine grained access rights according to SQL-standard

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