Is MongoDB good for full-text search?

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Is MongoDB good for full-text search?

One of the leading NoSQL databases, MongoDB is well known for its fast performance, versatile schema, scalability and great capabilities for indexing. Let us look at some context before we get into some details. Full-text search is an essential feature when we talk about finding content on the internet.

Why MongoDB is so popular?

MongoDB is popular among new developers due to it’s flexibility and ease of usage. Even though it’s easy to use it still provides all the capabilities needed to meet the complex requirements of modern applications. A lot of developers like Mongo because it stores all of it’s documents in JSON.

How does MongoDB text search work?

MongoDB text search uses the Snowball stemming library to reduce words to an expected root form (or stem) based on common language rules. Algorithmic stemming provides a quick reduction, but languages have exceptions (such as irregular or contradicting verb conjugation patterns) that can affect accuracy.

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Why elastic search is faster than MongoDB?

ElasticSearch is capable to handle queries through REST API and this is its advantage over MongoDB. Flat documents can easily be stored and without degrading the performance of the entire database. In addition to this, ElasticSearch is capable to handle data through filters.

Is it possible to implement a fulltext search Using NoSQL?

None of the existing “NoSQL” database provides a reasonable implementation of something that could be named “fulltext search”.

Why is there no analytical tooling for NoSQL databases?

It is simple: the NoSQL databases analytical tooling is almost nonexistent. A lot of data is packed into these databases, but the legacy analytics tooling hat is based on the relational technology cannot make any sense of it, because it is tabular and uniform data.

What are the different types of NoSQL databases?

Types of NoSQL databases include pure document databases, key-value stores, wide-column databases, and graph databases. NoSQL databases are built from the ground up to store and process vast amounts of data at scale and support a growing number of modern businesses.

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How does full-text search work?

Full-text search is powered by the Full-Text Engine. The Full-Text Engine has two roles: indexing support and querying support. When a full-text population (also known as a crawl) is initiated, the Full-Text Engine pushes large batches of data into memory and notifies the filter daemon host.