DBMS > Badger vs. Hawkular Metrics vs. HyperSQL vs. OpenEdge vs. Prometheus

System Properties Comparison Badger vs. Hawkular Metrics vs. HyperSQL vs. OpenEdge vs. Prometheus

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Application development environment with integrated database management system

Open-source Time Series DBMS and monitoring system

Primary database model

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Website

github.com/dgraph-io/badger

www.hawkular.org

hsqldb.org

www.progress.com/openedge

prometheus.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

hsqldb.org/web/hsqlDocsFrame.html

documentation.progress.com/output/ua/OpenEdge_latest

prometheus.io/docs

Developer

DGraph Labs

Community supported by Red Hat

Progress Software Corporation

Initial release

2017

2014

2001

1984

2015

Current release

2.7.2, June 2023

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

based on BSD license

commercial

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

All OS with a Java VM

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

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

APIs and other access methods

HTTP REST

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC
Java

Progress proprietary ABL (Advanced Business Language)

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

Server-side scripts

Stored procedures

Java, SQL

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

none

Source-replica replication

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

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

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

Users and groups

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

Recent citations in the news

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

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

provided by Google News

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

What's New in OpenEdge 12.8
15 April 2024, release.nl

Learning to failover
3 April 2017, SDTimes.com

4 sources of latency and how to avoid them
1 November 2017, InfoWorld

provided by Google News

Introducing the Amazon Timestream for LiveAnalytics Prometheus Connector
8 July 2024, AWS Blog

How to Monitor an Ubuntu Server With Prometheus: Collecting and Visualizing System Metrics
9 July 2024, Linux Journal

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus
10 March 2024, AWS Blog

Consider Grafana vs. Prometheus for your time-series tools
18 October 2021, TechTarget

My Prometheus is Overwhelmed! Help!
24 July 2021, hackernoon.com

provided by Google News

Share this page