DBMS > Hawkular Metrics vs. Hyprcubd vs. OpenEdge vs. SAP HANA vs. TimescaleDB

System Properties Comparison Hawkular Metrics vs. Hyprcubd vs. OpenEdge vs. SAP HANA vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Serverless Time Series DBMS

Application development environment with integrated database management system

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

www.hawkular.org

hyprcubd.com (offline)

www.progress.com/openedge

www.sap.com/products/hana.html

www.timescale.com

Technical documentation

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

documentation.progress.com/output/ua/OpenEdge_latest

help.sap.com/hana

docs.timescale.com

Developer

Community supported by Red Hat

Hyprcubd, Inc.

Progress Software Corporation

SAP

Timescale

Initial release

2014

1984

2010

2017

Current release

OpenEdge 12.2, March 2020

2.0 SPS07 (April 4, 2023), April 2023

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based 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

hosted

AIX
HP-UX
Linux
Solaris
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

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

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

SQL-like query language

yes

close to SQL 92

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP REST

gRPC (https)

JDBC
ODBC

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

Supported programming languages

Go
Java
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

SQLScript, R

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

horizontal partitioning

since Version 11.4

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

yes

Source-replica replication with hot standby and reads on replicas

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

Eventual Consistency

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

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

token access

Users and groups

yes

fine grained access rights according to SQL-standard

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