DBMS > Hyprcubd vs. Prometheus vs. SiteWhere

System Properties Comparison Hyprcubd vs. Prometheus vs. SiteWhere

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Editorial information provided by DB-Engines

Name

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

Description

Serverless Time Series DBMS

Open-source Time Series DBMS and monitoring system

M2M integration platform for persisting/querying time series data

Primary database model

Time Series DBMS

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

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

hyprcubd.com (offline)

prometheus.io

github.com/sitewhere/sitewhere

Technical documentation

prometheus.io/docs

sitewhere1.sitewhere.io/index.html

Developer

Hyprcubd, Inc.

SiteWhere

Initial release

2015

2010

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

predefined scheme

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

Secondary indexes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

gRPC (https)

RESTful HTTP/JSON API

HTTP REST

Supported programming languages

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

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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.

User concepts

Access control

token access

Users with fine-grained authorization concept

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