DBMS > Microsoft Azure AI Search vs. Oracle NoSQL vs. ReductStore

System Properties Comparison Microsoft Azure AI Search vs. Oracle NoSQL vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Search-as-a-service for web and mobile app development

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Search engine

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Vector DBMS

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

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

azure.microsoft.com/en-us/services/search

www.oracle.com/database/nosql/technologies/nosql

github.com/reductstore
www.reduct.store

Technical documentation

learn.microsoft.com/en-us/azure/search

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.reduct.store/docs

Developer

Microsoft

Oracle

ReductStore LLC

Initial release

2015

2011

2023

Current release

23.3, December 2023

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Business Source License 1.1

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

C++, Rust

Server operating systems

hosted

Linux
Solaris SPARC/x86

Docker
Linux
macOS
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

HTTP API

Supported programming languages

C#
Java
JavaScript
Python

C
C#
Go
Java
JavaScript (Node.js)
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

yes

using Azure authentication

Access rights for users and roles

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