Quiz 2: Index and Atlas Data Platform

MongoDB Atlas can support the following formats of data

• Time series

• Geo-spatial

• Key-value pair

• All of the given

Challenges of a bolt on(dedicated) search engine includes

• All of the given

• Setup and maintain a new technology

• ETL of data to search platform

• Stale data

The three layers of GenAI stack, MongoDB helps at 'Tooling and data to fine-tune and build apps'

• True

• False

Choose the incorrect option

• MongoDB has integration with Langchain, Hugging Face, Llama index etc

• GenAI can be used for Better Customer Experience 

  • Hyper personalization

• The only way to store vector data is a dedicated vector database

• RAG helps to add context to your queries to LLM

Atlas for Edge provides bidirectional data synchronisation

• True

• False

The rule for indexing is

• Equality, Range, Sort

• Sort, Equality, Range

• Range, Equality, Sort

• Equality, Sort, Range

This is NOT a type of Index in MongoDB

• Multi-key index

• Shard index

• Geo-spatial index

• Text index

stage : 'COLLSCAN' in the explain plan shows

• The query is using index

• Cannot infer anything

• There are no index built on the collection

• The query is not using index

Choose the correct statement.

• Indexes are not compressed

• Indexes are compressed same as data

• Indexes have a special compressed format

• Node of the given

MongoDB allows upto 64 indexes, so we should create as many as we can to get good performance

• True

• False