CouchDB Basics

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12 Reviews


DARSHAN SULAKHE

good 2022-06-11

Jhemar Denuevo

Wow okay 2022-05-19

Jayniel Morente

good job 2022-05-04

Vincent John E.Buhay

Excellent 2022-04-30

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Course Description

Apache CouchDB Software Apache CouchDB is an open-source document-oriented NoSQL database, implemented in Erlang. CouchDB uses multiple formats and protocols to store, transfer, and process its data, it uses JSON to store data, JavaScript as its query language using MapReduce, and HTTP for an API. What is CouchDB used for? Apache CouchDB (CouchDB) is an open source NoSQL document database that collects and stores data in JSON-based document formats. Unlike relational databases, CouchDB uses a schema-free data model, which simplifies record management across various computing devices, mobile phones, and web browsers. What is the difference between MongoDB and CouchDB? The 5 most important differences between CouchDB and MongoDB are: Queries: CouchDB accepts queries via a RESTful HTTP API, while MongoDB has its own query language. CAP theorem: CouchDB prioritizes availability, while MongoDB prioritizes consistency. ... Reviews: MongoDB seems to have somewhat better reviews than CouchDB. Is CouchDB SQL database? This is a collection of some common SQL queries and how to get the same result in CouchDB. The key to remember here is that CouchDB does not work like an SQL database at all, and that best practices from the SQL world do not translate well or at all to CouchDB. Is CouchDB an acid? CouchDB is ACID compliant. Within a CouchDB server, for a single document update, CouchDB has the properties of atomicity, consistency, isolation, and durability (ACID). ... Basically, this will cause CouchDB to do an explicit fsync after each operation (which is very expensive and slow) Is Redis faster than MongoDB? What is no SQL DB? NoSQL databases (aka "not only SQL") are non tabular, and store data differently than relational tables. NoSQL databases come in a variety of types based on their data model. ... They provide flexible schemas and scale easily with large amounts of data and high user loads.