DBMS > Hawkular Metrics vs. Oracle Rdb vs. Prometheus vs. Sadas Engine vs. Stardog

System Properties Comparison Hawkular Metrics vs. Oracle Rdb vs. Prometheus vs. Sadas Engine vs. Stardog

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.

Open-source Time Series DBMS and monitoring system

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.hawkular.org

www.oracle.com/database/technologies/related/rdb.html

prometheus.io

www.sadasengine.com

www.stardog.com

Technical documentation

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

www.oracle.com/database/technologies/related/rdb-doc.html

prometheus.io/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.stardog.com

Developer

Community supported by Red Hat

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

Stardog-Union

Initial release

2014

1984

2015

2006

2010

Current release

7.4.1.1, 2021

8.0

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

commercial

free trial version available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Java

Server operating systems

Linux
OS X
Windows

HP Open VMS

Linux
Windows

AIX
Linux
Windows

Linux
macOS
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

HTTP REST

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Go
Java
Python
Ruby

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via Hawkular Alerting

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

by Federation

none

Multi-source replication in HA-Cluster

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

none

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

yes, on a single node

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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