DBMS > H2 vs. Hawkular Metrics vs. LevelDB vs. OpenQM

System Properties Comparison H2 vs. Hawkular Metrics vs. LevelDB vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

www.h2database.com

www.hawkular.org

github.com/google/leveldb

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

www.h2database.com/html/main.html

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

github.com/google/leveldb/blob/main/doc/index.md

Developer

Thomas Mueller

Community supported by Red Hat

Google

Rocket Software, originally Martin Phillips

Initial release

2005

2014

2011

1993

Current release

2.2.220, July 2023

1.23, February 2021

3.4-12

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPLv2, extended commercial license available

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

All OS with a Java VM

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

Typing

predefined data types such as float or date

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

HTTP REST

Supported programming languages

Java

Go
Java
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Access rights can be defined down to the item level

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