DBMS > Hawkular Metrics vs. PostGIS vs. searchxml vs. TimescaleDB vs. XTDB

System Properties Comparison Hawkular Metrics vs. PostGIS vs. searchxml vs. TimescaleDB vs. XTDB

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

DBMS for structured and unstructured content wrapped with an application server

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Spatial DBMS

Native XML DBMS
Search engine

Time Series DBMS

Document store

Secondary database models

Relational DBMS

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

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	23.90
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

www.hawkular.org

postgis.net

www.searchxml.net/category/products

www.timescale.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

postgis.net/documentation

www.searchxml.net/support/handouts

docs.timescale.com

www.xtdb.com/docs

Developer

Community supported by Red Hat

informationpartners gmbh

Timescale

Juxt Ltd.

Initial release

2014

2005

2015

2017

2019

Current release

3.4.2, February 2024

1.0

2.13.0, November 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL v2.0

commercial

Open Source

Apache 2.0

Open Source

MIT License

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++

Clojure

Server operating systems

Linux
OS X
Windows

Windows

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes, extensible-data-notation format

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

full PostgreSQL SQL syntax

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

RESTful HTTP API
WebDAV
XQuery
XSLT

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

HTTP REST
JDBC

Supported programming languages

Go
Java
Python
Ruby

C++

most other programming languages supported via APIs

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

on the application server

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

none

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

based on PostgreSQL

yes

sychronisation to multiple collections

Source-replica replication with hot standby and reads on replicas

yes, each node contains all data

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

yes

based on PostgreSQL

Domain, group and role-based access control at the document level and for application services

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, azure.microsoft.com

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

provided by Google News

Share this page