Lunch & Learn | MongoDB - Atlas Search

I recently attended an insightful Lunch and Learn Session hosted by MongoDB.

I got various insights on MongoDB’s developer data platform, which extends the core technology of MongoDB to support additional application data workloads like search, mobile and edge data, real-time analytics, and data engineering.

I also had hands-on experience on MongoDB's developer data platform, leveraging Atlas Search for fast, relevance-based search capabilities. Was excited to see how MongoDB extends its core technology to support various application data workloads.'

In the workshop, I learned about Atlas Search, which combines the power of Apache Lucene, the technology behind the world’s most popular search engines.

I got insights on various topics on MongoDB but I would like to mention key differences between database query and search query in this article

Database Query

When should one use a database query?

• Developers know what queries will look like

• Index specific fields based on common query patterns

• Optimized for correctness and integrity

Example: “How many unique people have viewed a particular video in the past 7 days?”

Search Query

When should one use a search query?

• Developers don’t know what queries look like in advance

• Index many fields that may be searched across

• Optimized for speed, relevance, and navigation

Example: “Show me the most popular cricket videos in the NCR area.”

I hope you found this useful. Like this post and follow me for more such content. If you want more insights on such topics as to Mongo DB, Atlas Search, internalization, etc let me know in the comments below

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