DBMS > Amazon Redshift vs. Manticore Search vs. Oracle Rdb vs. OushuDB

System Properties Comparison Amazon Redshift vs. Manticore Search vs. Oracle Rdb vs. OushuDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Multi-storage database for search, including full-text search.

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Website

aws.amazon.com/redshift

manticoresearch.com

www.oracle.com/database/technologies/related/rdb.html

www.oushu.com/product/oushuDB

Technical documentation

docs.aws.amazon.com/redshift

manual.manticoresearch.com

www.oracle.com/database/technologies/related/rdb-doc.html

www.oushu.com/documentation

Developer

Amazon (based on PostgreSQL)

Manticore Software

Oracle, originally developed by Digital Equipment Corporation (DEC)

Oushu

Initial release

2012

2017

1984

Current release

6.0, February 2023

7.4.1.1, 2021

4.0.1, August 2020

License

Commercial or Open Source

commercial

Open Source

GPL version 2

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++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

HP Open VMS

Linux

Data scheme

yes

Fixed schema

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

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

restricted

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

yes

isolated transactions for atomic changes and binary logging for safe writes

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

Kerberos, SSL and role based access

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