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NoSQL Databases and Their Use Cases

KDnuggets

Learn about NoSQL Databases and their types like key-value, document, graph and column family with their use cases.

Database 313
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CRUD Operations in MongoDB

Analytics Vidhya

Introduction MongoDB is a type of NoSQL Database, that stores data in document format(bson or binary json format). Its advantage over traditional SQL Databases includes the flexibility of schema-design, relaxation of its ACID properties and its distributed data storage capability thus performing better for […].

SQL 351
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Endatabas: An open source immutable, Document Database with Full History

Hacker News

SQL Document Database with Full History

Database 157
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How To Create An Aggregation Pipeline In MongoDB

Analytics Vidhya

Introduction MongoDB is a free open-source No-SQL document database. ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post How To Create An Aggregation Pipeline In MongoDB appeared first on Analytics Vidhya.

SQL 319
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Introduction to Elasticsearch using Python

Analytics Vidhya

Introduction Elasticsearch is primarily a document-based NoSQL database, meaning developers do not need any prior knowledge of SQL to use it. Still, it is much more than just a NoSQL database. This article was published as a part of the Data Science Blogathon.

Python 318
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Understanding databases: A comprehensive guide to different types for beginners

Data Science Dojo

While Python and R are popular for analysis and machine learning, SQL and database management are often overlooked. However, data is typically stored in databases and requires SQL or business intelligence tools for access. Through this guide, we give you a larger picture to get started with your database journey.

Database 195
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Unify structured data in Amazon Aurora and unstructured data in Amazon S3 for insights using Amazon Q

AWS Machine Learning Blog

Whether it’s structured data in databases or unstructured content in document repositories, enterprises often struggle to efficiently query and use this wealth of information. The solution combines data from an Amazon Aurora MySQL-Compatible Edition database and data stored in an Amazon Simple Storage Service (Amazon S3) bucket.

Database 112