DBMS > Amazon Redshift vs. FatDB vs. Oracle Coherence vs. YDB

System Properties Comparison Amazon Redshift vs. FatDB vs. Oracle Coherence vs. YDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Oracles in-memory data grid solution

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

Document store
Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

aws.amazon.com/redshift

www.oracle.com/java/coherence

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.aws.amazon.com/redshift

docs.oracle.com/en/middleware/standalone/coherence

ydb.tech/en/docs

Developer

Amazon (based on PostgreSQL)

FatCloud

Oracle

Yandex

Initial release

2012

2007

2019

Current release

14.1, August 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0; commercial license 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

Windows

All OS with a Java VM

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

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

Via inetgration in SQL Server

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JCache
JPA
RESTful HTTP API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C++
Java

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

via applications

Triggers

yes

via applications

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes, with selectable consistency level

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

optionally

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

Can implement custom security layer via applications

authentification to access the cache via certificates or http basic authentication

Access rights defined for Yandex Cloud users

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