DBMS > EXASOL vs. IRONdb vs. SiteWhere vs. VelocityDB

System Properties Comparison EXASOL vs. IRONdb vs. SiteWhere vs. VelocityDB

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

M2M integration platform for persisting/querying time series data

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS
Object oriented DBMS

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Score	0.11
Rank	#347	Overall
	#35	Graph DBMS
	#15	Object oriented DBMS

Website

www.exasol.com

www.circonus.com/solutions/time-series-database/

github.com/sitewhere/sitewhere

velocitydb.com

Technical documentation

www.exasol.com/resources

docs.circonus.com/irondb/category/getting-started

sitewhere1.sitewhere.io/index.html

velocitydb.com/UserGuide

Developer

Exasol

Circonus LLC.

SiteWhere

VelocityDB Inc

Initial release

2000

2017

2010

2011

Current release

V0.10.20, January 2018

7.x

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

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

C and C++

Java

Server operating systems

Linux

Linux
OS X
Windows

Any that supports .NET

Data scheme

yes

schema-free

predefined scheme

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HTTP API

HTTP REST

.Net

Supported programming languages

Java
Lua
Python
R

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

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

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

Users with fine-grained authorization concept

Based on Windows Authentication

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