Engineering Atlasby Abhishek Goyal

Tag

Elasticsearch

6 diagram-led guides on Elasticsearch by Abhishek Goyal.

  1. GuideNew

    How Search Works in System Design: The Full Journey of a Query

    Follow one search query, "cheap flights goa", through 14 stops: browser, DNS, CDN, load balancer, app server, Redis cache, Elasticsearch coordinator, shards, inverted index, page cache and SSD, then back. Learn the latency numbers that matter, how a new record reaches the index (WAL, CDC, Kafka, refresh), what breaks, and how to present search in an HLD interview.

    ~20 min read · Beginner → Senior · 4 diagrams

  2. Deep diveNew

    How Search Engines Work: Inverted Index, Text Analysis, TF-IDF and BM25

    How a full-text search engine finds and ranks results: the inverted index, text analysis (tokenising, stemming, stop words), postings lists and boolean queries, TF-IDF and BM25 scoring, Lucene segments and merges, and near-real-time refresh, explained from the book-index analogy up to system design interview answers.

    ~25 min read · Beginner → Senior · 6 diagrams

  3. Deep diveNewMembers

    Types of Search in System Design: Autocomplete, Fuzzy, Phrase, Geo, Faceted, Vector and Hybrid

    The seven kinds of search behind one search box, for system design interviews: autocomplete with edge n-grams and FSTs, fuzzy search with Levenshtein automata, phrase search with positions, geo search with cells and BKD trees, faceted search and why counts are approximate across shards, vector search with HNSW, and hybrid search merged with Reciprocal Rank Fusion.

    ~16 min read · Beginner → Senior · 5 diagrams

  4. Deep diveNewMembers

    Elasticsearch for System Design: Shards, Replicas, Write Path and Read Path

    How Elasticsearch works inside, for system design interviews: cluster, nodes, shards and replicas, document routing, the write path (translog, refresh, flush, merge) and why search is near real-time, query-then-fetch scatter-gather, mappings, shard sizing, CDC and outbox sync from your database, and the tuning mistakes that hurt in production.

    ~25 min read · Beginner → Senior · 5 diagrams

  5. Deep diveNewMembers

    Choosing a Search Engine: Elasticsearch vs Postgres vs Redis vs OpenSearch, Solr and Typesense

    How to choose a search engine in system design: what a separate search cluster really costs, real full-text search in Postgres with tsvector, GIN and pg_trgm, Redis Search and MongoDB Search, the Lucene family (Elasticsearch, OpenSearch, Solr), Typesense, Meilisearch and Vespa, and a decision flow you can defend in an interview.

    ~14 min read · Beginner → Senior · 3 diagrams

  6. Deep diveNewMembers

    Search System Design Case Studies: Discord, GitHub, LinkedIn, Uber, Pinterest and More

    Real-world search system design case studies for HLD interviews: how Discord, GitHub, LinkedIn, Uber, DoorDash, Yelp, Instacart, Pinterest, Twitter, Slack, eBay and others scaled Elasticsearch, built their own Lucene engines, added vector and hybrid search, and ranked results, with the patterns that repeat.

    ~18 min read · Beginner → Senior · 7 diagrams

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