DBMS > Amazon Redshift vs. Valentina Server vs. YTsaurus

System Properties Comparison Amazon Redshift vs. Valentina Server vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Object-relational database and reports server

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Relational DBMS

Document store
Key-value store

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

Score	14.52
Rank	#38	Overall
	#23	Relational DBMS

Score	0.14
Rank	#326	Overall
	#146	Relational DBMS

Score	0.17
Rank	#314	Overall
	#46	Document stores
	#44	Key-value stores

Website

aws.amazon.com/redshift

www.valentina-db.net

ytsaurus.tech

Technical documentation

docs.aws.amazon.com/redshift

valentina-db.com/docs/dokuwiki/v5/doku.php

ytsaurus.tech/docs/en

Developer

Amazon (based on PostgreSQL)

Paradigma Software

Yandex

Initial release

2012

1999

2023

Current release

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

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

C++

Server operating systems

hosted

Linux
OS X
Windows

Ubuntu

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

YQL, an SQL-based language, is supported

APIs and other access methods

JDBC
ODBC

ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

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 Control Lists

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