DBMS > Amazon Redshift vs. IRONdb vs. UniData,UniVerse vs. Yaacomo

System Properties Comparison Amazon Redshift vs. IRONdb vs. UniData,UniVerse vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Large scale data warehouse service for use with business intelligence tools

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

aws.amazon.com/redshift

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

yaacomo.com

Technical documentation

docs.aws.amazon.com/redshift

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

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Amazon (based on PostgreSQL)

Circonus LLC.

Rocket Software

Q2WEB GmbH

Initial release

2012

2017

1985

2009

Current release

V0.10.20, January 2018

License

Commercial or Open Source

commercial

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

C and C++

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

optional

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

yes

APIs and other access methods

JDBC
ODBC

HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in Lua

yes

Triggers

yes

U2 Basic

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

configurable

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

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

fine grained access rights according to SQL-standard

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