--- title: "#bloom-filter articles | Hashnode" description: "Explore 40 articles tagged #bloom-filter on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/bloom-filter" --- Tag # #bloom-filter 40 posts · 3 followers [Parminder singh](https://hashnode.com/@param007) · [Nov 4](https://hashnode.com/posts/bloom-filter-username-check/6aeaf0ffd499967824bc7def) ### [How Instagram checks 1 billion usernames and tells you in milliseconds if yours is free](https://systemdesignwithparam.hashnode.dev/bloom-filter-username-check?utm_source=hashnode&utm_medium=feed) You type rahul\_07 on a signup page. Before you finish, it says "This username isn't available." Now imagine 1 billion users and a check on every keystroke. Sending every check to the database creates 9 min read · [systemdesignwithparam.hashnode.dev](https://systemdesignwithparam.hashnode.dev/bloom-filter-username-check?utm_source=hashnode&utm_medium=feed) [Oluwaseyi Fatunmole](https://hashnode.com/@foluwaseyi) · [Aug 31](https://hashnode.com/posts/bloom-filters-explained/6a95f9a98577dd0ab849ab46) ### [Bloom Filters Explained: The Probabilistic Data Structure Powering Instagram, Google, and High-Scale Systems](https://freecodecamp.org/news/bloom-filters-explained?utm_source=hashnode&utm_medium=feed) Instagram has over 500 million registered usernames. When a new user tries to register, the platform needs to answer one question almost instantly: has this username already been taken? The naïve answ 19 min read · [freecodecamp.org](https://freecodecamp.org/news/bloom-filters-explained?utm_source=hashnode&utm_medium=feed) [Victor Alekseev](https://hashnode.com/@krocodl) · [Jul 3](https://hashnode.com/posts/teleport-en/6a47656df5256fa54490c38f) ### [Database synchronization based on Invertible Bloom Filters](https://krocodl.hashnode.dev/teleport-en?utm_source=hashnode&utm_medium=feed) Deep dive into Invertible Bloom Filters: the math behind Fivetran's Teleport Sync, peeling decode, rowHash design, and comparison to CDC. 61 min read · [krocodl.hashnode.dev](https://krocodl.hashnode.dev/teleport-en?utm_source=hashnode&utm_medium=feed) [Abstract Algorithms](https://hashnode.com/@abstractalgorithms) · [Jul 2](https://hashnode.com/posts/bloom-filter-membership-byte/6a45c4e019a53d5d37e80511) ### [Bloom Filter Membership](https://abstractalgorithms.hashnode.dev/bloom-filter-membership-byte?utm_source=hashnode&utm_medium=feed) Learn how this probabilistic data structure offers instant set membership checks with zero false negatives. 1 min read · [abstractalgorithms.hashnode.dev](https://abstractalgorithms.hashnode.dev/bloom-filter-membership-byte?utm_source=hashnode&utm_medium=feed) [Prasanth Madhurapantula](https://hashnode.com/@catalysed) · [Jun 29](https://hashnode.com/posts/how-bloom-filters-work-build-one-from-scratch-python/6a4286cee47e505c8beef4bb) ### [How a Bloom Filter Works: Build One From Scratch in Python](https://freecodecamp.org/news/how-bloom-filters-work-build-one-from-scratch-python?utm_source=hashnode&utm_medium=feed) A Bloom filter gives you something that feels like magic: it can tell you whether an item is in a set of billions, using only a few kilobytes of memory. And it answers in the same tiny amount of time 12 min read · [freecodecamp.org](https://freecodecamp.org/news/how-bloom-filters-work-build-one-from-scratch-python?utm_source=hashnode&utm_medium=feed) [Ritik Singh](https://hashnode.com/@DevDarkLord) · [May 3](https://hashnode.com/posts/the-art-of-the-maybe-scaling-systems-with-bloom-filters/69f766c50ab374db99d5cb5f) ### [The Art of the "Maybe": Scaling Systems with Bloom Filters](https://ritik-singh-rajput.hashnode.dev/the-art-of-the-maybe-scaling-systems-with-bloom-filters?utm_source=hashnode&utm_medium=feed) How to save gigabytes of memory and boost database performance using probabilistic data structures. 12 min read · [ritik-singh-rajput.hashnode.dev](https://ritik-singh-rajput.hashnode.dev/the-art-of-the-maybe-scaling-systems-with-bloom-filters?utm_source=hashnode&utm_medium=feed) [Abstract Algorithms](https://hashnode.com/@abstractalgorithms) · [May 3](https://hashnode.com/posts/bloom-filters-explained/69f6f914e586d254c538be0e) ### [Bloom Filters Explained: Membership Testing with Zero False Negatives](https://abstractalgorithms.hashnode.dev/bloom-filters-explained?utm_source=hashnode&utm_medium=feed) How a bit array and k hash functions answer 'definitely not in this set' in O(1) — and why false negatives are mathematically impossible. 19 min read · [abstractalgorithms.hashnode.dev](https://abstractalgorithms.hashnode.dev/bloom-filters-explained?utm_source=hashnode&utm_medium=feed) [Abhijit Gadhave](https://hashnode.com/@abhi87) · [May 1](https://hashnode.com/posts/the-magic-of-bloom-filters/69f45adf909e64ad079a7324) ### [The Magic of Bloom Filters](https://abhigadhave97.hashnode.dev/the-magic-of-bloom-filters?utm_source=hashnode&utm_medium=feed) Have you ever tried creating an account on Instagram, Twitter, or Gmail? You type a username like: Abhijit8 …and instantly you get: “Username already taken.” What’s interesting is not the message. I 4 min read · [abhigadhave97.hashnode.dev](https://abhigadhave97.hashnode.dev/the-magic-of-bloom-filters?utm_source=hashnode&utm_medium=feed) [Abstract Algorithms](https://hashnode.com/@abstractalgorithms) · [Apr 5](https://hashnode.com/posts/probabilistic-data-structures-explained/69d1c43d31bee94593d1b456) ### [Probabilistic Data Structures: A Practical Guide to Bloom Filters, HyperLogLog, and Count-Min Sketch](https://abstractalgorithms.hashnode.dev/probabilistic-data-structures-explained?utm_source=hashnode&utm_medium=feed) Trade exact answers for fixed memory and O(1) operations: a comparative guide to Bloom Filters, HyperLogLog, and Count-Min Sketch. 14 min read · [abstractalgorithms.hashnode.dev](https://abstractalgorithms.hashnode.dev/probabilistic-data-structures-explained?utm_source=hashnode&utm_medium=feed) [Abstract Algorithms](https://hashnode.com/@abstractalgorithms) · [Mar 9](https://hashnode.com/posts/how-bloom-filters-work/69ae362a0fe4dd6eff460430) ### [How Bloom Filters Work: The Probabilistic Set](https://abstractalgorithms.hashnode.dev/how-bloom-filters-work?utm_source=hashnode&utm_medium=feed) Can you check if a username is taken without querying the database? Yes. Bloom Filters are a space-efficient probabilistic data structure. 13 min read · [abstractalgorithms.hashnode.dev](https://abstractalgorithms.hashnode.dev/how-bloom-filters-work?utm_source=hashnode&utm_medium=feed)