DBMS > Hyprcubd vs. SiteWhere vs. Splunk

System Properties Comparison Hyprcubd vs. SiteWhere vs. Splunk

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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

M2M integration platform for persisting/querying time series data

Analytics Platform for Big Data

Primary database model

Time Series DBMS

Search engine

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

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

hyprcubd.com (offline)

github.com/sitewhere/sitewhere

www.splunk.com

Technical documentation

sitewhere1.sitewhere.io/index.html

docs.splunk.com/Documentation/Splunk

Developer

Hyprcubd, Inc.

SiteWhere

Splunk Inc.

Initial release

2010

2003

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

Limited free edition and free developer edition available

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
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

predefined scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

gRPC (https)

HTTP REST

Supported programming languages

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on HBase

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

Access rights for users and roles

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More resources

DB-Engines blog posts

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2 July 2014, Paul Andlinger

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