Today, I faced this challenge while structuring click events performed on a screen. The estimation shows that a single location could accumulate over 50K records or more.
So, the decision comes down to:
โข Should we use an ๐ฎ๐ฟ๐ฟ๐ฎ๐ ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ where ๐ฐ๐ฒ๐ป๐๐ฒ๐ฟ๐๐ฑ and ๐ฎ๐ฝ๐ฝ๐ผ๐ถ๐ป๐๐บ๐ฒ๐ป๐๐๐ฎ๐๐ฒ keep one dayโs record in a single document?
โข Or should we opt for ๐๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ฒ ๐ฑ๐ผ๐ฐ๐๐บ๐ฒ๐ป๐๐ for each transaction?
Letโs dive into what works best and why! ๐
๐๐ฒ๐ ๐๐ผ๐ป๐๐ถ๐ฑ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐:
- ๐ฆ๐ฐ๐ฎ๐น๐ฎ๐ฏ๐ถ๐น๐ถ๐๐ ๐ โข ๐๐ฟ๐ฟ๐ฎ๐๐: Risk of exceeding MongoDBโs 16 MB document size limit, making it unsuitable for large datasets. โข ๐ฆ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ฒ ๐๐ผ๐ฐ๐๐บ๐ฒ๐ป๐๐: Supports sharding, allowing data distribution across servers as the dataset grows, ensuring scalability.
- ๐ค๐๐ฒ๐ฟ๐ ๐ฃ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ โก โข ๐๐ฟ๐ฟ๐ฎ๐๐: MongoDB must scan entire arrays, which becomes inefficient as arrays grow. โข ๐ฆ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ฒ ๐๐ผ๐ฐ๐๐บ๐ฒ๐ป๐๐: Efficient querying with indexed fields like centerId and appointmentDate, enabling fast lookups and aggregations.
- ๐๐น๐ฒ๐ ๐ถ๐ฏ๐ถ๐น๐ถ๐๐ ๐ฎ๐ป๐ฑ ๐ ๐ฎ๐ถ๐ป๐๐ฒ๐ป๐ฎ๐ป๐ฐ๐ฒ ๐งฉ โข ๐๐ฟ๐ฟ๐ฎ๐๐: Modifying or deleting specific elements in large arrays can be cumbersome. โข ๐ฆ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ฒ ๐๐ผ๐ฐ๐๐บ๐ฒ๐ป๐๐: Easier to update or delete individual records, maintaining data integrity and consistency with minimal effort.
๐ง๐ต๐ฒ ๐๐ฒ๐๐ ๐๐ฝ๐ฝ๐ฟ๐ผ๐ฎ๐ฐ๐ต:
๐ฆ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ฒ ๐๐ผ๐ฐ๐๐บ๐ฒ๐ป๐๐: โ
:
โข ๐ช๐ต๐?
โข ๐ฆ๐ฐ๐ฎ๐น๐ฎ๐ฏ๐น๐ฒ: Easily handles large data volumes (50K+ records).
โข ๐๐ณ๐ณ๐ถ๐ฐ๐ถ๐ฒ๐ป๐: Supports indexing for fast, optimized queries.
โข ๐๐น๐ฒ๐
๐ถ๐ฏ๐น๐ฒ: Simplifies updates and modifications, focusing on individual records without affecting others.
Have you faced a similar scenario? Share your approach in the comments below!
Iโve created a detailed post on ๐ ๐ฒ๐ฑ๐ถ๐๐บ ๐ฏ๐น๐ผ๐ด with step-by-step instructions and code examples. Feel free to check it out!๐๏ธ๐๏ธ: https://lnkd.in/deGK3W4E
Please repost this ๐ if you find it useful. ๐ Follow Apurv Upadhyay โ๏ธ for more content like this
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