DBMS > Hawkular Metrics vs. HyperSQL vs. openGemini vs. Postgres-XL

System Properties Comparison Hawkular Metrics vs. HyperSQL vs. openGemini vs. Postgres-XL

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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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

www.hawkular.org

hsqldb.org

www.opengemini.org
github.com/openGemini

www.postgres-xl.org

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

docs.opengemini.org/guide

www.postgres-xl.org/documentation

Developer

Community supported by Red Hat

Huawei and openGemini community

Initial release

2014

2001

2022

2014

since 2012, originally named StormDB

Current release

2.7.2, June 2023

1.1, July 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

based on BSD license

Open Source

Apache Version 2.0

Open Source

Mozilla public 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

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

HTTP REST

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP REST

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

Supported programming languages

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC
Java

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Java, SQL

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

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

MVCC

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

Administrators and common users accounts

fine grained access rights according to SQL-standard

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