{"slug": "elasticsearch", "name": "Elasticsearch", "category": "search", "category_name": "Search", "description": "", "recommenders": 3, "commenters": 10, "warners": 1, "score": 3.219, "rising": 0.35, "first": "2025-11-04", "latest": "2026-10-02", "why": "found its speed, capabilities, and simplicity all significant improvements compared to the MariaDB-based search", "why_is_quote": true, "has_verdict": false, "sentiment": {"recommend": 3, "neutral": 4, "compare": 2, "warn": 1}, "spark": [0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1], "listed": true, "loved": [], "caveat": "", "short_quote": "found its speed, capabilities, and simplicity all significant improvements compared to the MariaDB-based search", "icon": true, "domain": "elastic.co", "github_repo": null, "official_url": "https://www.elastic.co/elasticsearch", "pricing": "", "aliases": ["Elasticsearch"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 798881136, "item_id": 49930071, "url": "https://news.ycombinator.com/item?id=49930071", "by": "_kidlike", "date": "2026-10-02", "stance": "recommend", "quote": "for the same reason we used ElasticSearch for vector search, because it's just one part of a query.", "excerpt": "for the same reason we used ElasticSearch for vector search, because it's just one part of a query. Everything else we already had (filters etc), just stay and can be combined with vector search.", "context": "", "use_case": "vector search with filters", "switched_from": "", "story": "RIP, vector database"}, {"id": 750523489, "item_id": 46907718, "url": "https://news.ycombinator.com/item?id=46907718", "by": "tempestn", "date": "2026-02-05", "stance": "recommend", "quote": "found its speed, capabilities, and simplicity all significant improvements compared to the MariaDB-based search", "excerpt": "It really depends on your use case, doesn't it? I'd say, just use Postgres... until you have a reason not to. We used finally switched to Elasticsearch to power user search queries of our vehicle listings a few years ago, and found its speed, capabilities, and simplicity all significant improvements compared to the MariaDB-based search we'd been using previously. (Postgres's search features are likely better than Mar", "context": "runs a vehicle listings product", "use_case": "user search for vehicle listings", "switched_from": "MariaDB", "story": "It's 2026, Just Use Postgres"}, {"id": 742019059, "item_id": 46376191, "url": "https://news.ycombinator.com/item?id=46376191", "by": "1103938364", "date": "2025-12-24", "stance": "recommend", "quote": "L2: Elasticsearch fallback with Painless scripting to score offline users", "excerpt": "Hello HN! I'm the author of SoakUpTheSun. This is an open-source visual assistance platform I built to connect visually impaired users with volunteers via real-time video (similar to \"Be My Eyes\", but open-source). I built this primarily to learn how to handle high-concurrency scenarios and heterogeneous microservices. Key technical implementation details: Custom SFU in Go: Instead of using standard media servers, I ", "context": "", "use_case": "fallback offline user scoring", "switched_from": "", "story": "Show HN: Opensource\"BeMyEyes\"alternative(Java/Go/Python)built as a learning pjet"}]}], "caveats": [{"label": "", "summary": "", "quotes": [{"id": 746389136, "item_id": 46649321, "url": "https://news.ycombinator.com/item?id=46649321", "by": "unethical_ban", "date": "2026-01-16", "stance": "warn", "quote": "I would never. Ever. Bet my savings on ES being stable enough to always be online to take in data, or predictable in retaining the data it took in.", "excerpt": "I work in infosec and several popular platforms use elasticsearch for log storage and analysis. I would never. Ever. Bet my savings on ES being stable enough to always be online to take in data, or predictable in retaining the data it took in. It feels very best-effort and as a consultant, I recommend orgs use some other system for retaining their logs, even a raw filesystem with rolling zips, before relying on ES un", "context": "works in infosec as a consultant", "use_case": "log storage and analysis", "switched_from": "", "story": "Elasticsearch Was Never a Database"}]}], "who": [{"by": "macnod", "context": "Senior software engineer, 20+ years", "url": "https://news.ycombinator.com/item?id=49922610", "date": "2026-10-01"}, {"by": "steinvakt2", "context": "sold a SaaS for media transcription and search", "url": "https://news.ycombinator.com/item?id=47149365", "date": "2026-02-25"}, {"by": "tempestn", "context": "runs a vehicle listings product", "url": "https://news.ycombinator.com/item?id=46907718", "date": "2026-02-05"}], "tags": [], "use_cases": ["vector search with filters", "search on azure government", "search engine", "querying data with llm", "indexing transcripts for search", "user search for vehicle listings"], "compared": [{"slug": "postgresql", "name": "PostgreSQL", "co": 2, "switched_from": 0, "switched_to": 1}, {"slug": "mariadb", "name": "MariaDB", "co": 1, "switched_from": 1, "switched_to": 0}, {"slug": "redis", "name": "Redis", "co": 2, "switched_from": 0, "switched_to": 0}], "makers": [{"id": 778737072, "item_id": 48671067, "url": "https://news.ycombinator.com/item?id=48671067", "by": "jedr", "date": "2026-06-25", "stance": "recommend", "quote": "Elastic is in fact open source again.", "excerpt": "(Elastic employee here) Elastic is in fact open source again. - Was originally open source Apache license - Switched to non-open source Elastic license in Jan 2021 [^1] - Switched to open source AGPL license in Aug 2024 [^2] Not to defend the license change(s). [1] https://www.elastic.co/blog/licensing-change [2] https://www.elastic.co/blog/elasticsearch-is-open-source-again", "context": "Elastic employee", "use_case": "search", "switched_from": "", "story": "Elastic lays off 7% of employees"}], "threads": [{"url": "https://news.ycombinator.com/item?id=46579954", "title": "Elasticsearch Was Never a Database", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=49923466", "title": "RIP, vector database", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49922568", "title": "Ask HN: Who wants to be hired? (October 2026)", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=48666100", "title": "Elastic lays off 7% of employees", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=48382047", "title": "Redis 8.8: New array data structure, rate limiter, performance improvements", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=47712718", "title": "I Still Prefer MCP over Skills", "mentions": 1}], "sentiment_by_month": {"2025-11": {"compare": 1}, "2025-12": {"recommend": 1}, "2026-01": {"warn": 1, "neutral": 1}, "2026-02": {"recommend": 1, "neutral": 1}, "2026-03": {}, "2026-04": {"neutral": 1}, "2026-05": {}, "2026-06": {"compare": 1}, "2026-07": {}, "2026-08": {}, "2026-09": {}, "2026-10": {"neutral": 1, "recommend": 1}}, "quotes": [{"id": 798881136, "item_id": 49930071, "url": "https://news.ycombinator.com/item?id=49930071", "by": "_kidlike", "date": "2026-10-02", "stance": "recommend", "quote": "for the same reason we used ElasticSearch for vector search, because it's just one part of a query.", "excerpt": "for the same reason we used ElasticSearch for vector search, because it's just one part of a query. Everything else we already had (filters etc), just stay and can be combined with vector search.", "context": "", "use_case": "vector search with filters", "switched_from": "", "story": "RIP, vector database"}, {"id": 798761761, "item_id": 49922610, "url": "https://news.ycombinator.com/item?id=49922610", "by": "macnod", "date": "2026-10-01", "stance": "neutral", "quote": "commercial Elasticsearch was not allowed, so I replaced it with self-hosted Elasticsearch inside the VNet", "excerpt": "Location: Manteca, CA, USA Remote: Yes (required) Willing to relocate: No Technologies: Python, Java, SQL, AWS, Azure, Kubernetes, Terraform, PostgreSQL, GitHub Actions, Common Lisp R\u00e9sum\u00e9/CV: https://sinistercode.com/public/donnie/resume Email: macnod [at] gmail [dot] com Senior software engineer, 20+ years. Available immediately; US Pacific hours. Looking for a full-time remote role designing backend or platform sy", "context": "Senior software engineer, 20+ years", "use_case": "search on Azure Government", "switched_from": "", "story": "Ask HN: Who wants to be hired? (October 2026)"}, {"id": 774609763, "item_id": 48413110, "url": "https://news.ycombinator.com/item?id=48413110", "by": "jillesvangurp", "date": "2026-06-05", "stance": "compare", "quote": "Same with Elasticsearch vs. Opensearch", "excerpt": "We switched to Valkey two years ago. I haven't really looked back. I think both projects have done a lot of nice stuff since the split but it's not really impacting anything I use. The feature set was fine five years ago and I don't think we're using anything in Valkey that wouldn't work in Redis. There are probably a lot of projects that never switched over because they had no real need. But most of the cloud provid", "context": "", "use_case": "search engine", "switched_from": "", "story": "Redis 8.8: New array data structure, rate limiter, performance improvements"}, {"id": 763431920, "item_id": 47714495, "url": "https://news.ycombinator.com/item?id=47714495", "by": "Xenoamorphous", "date": "2026-04-09", "stance": "neutral", "quote": "if I have some ElasticSearch cluster, I use a skill to describe the data", "excerpt": "I use both and don't feel they're mutually exclusive. E.g. if I have some ElasticSearch cluster, I use a skill to describe the data, and if I ask the LLM to write code that queries ElasticSearch but to test it first it can use a combination of skill + MCP to actually run a query. I think this model works nicely.", "context": "", "use_case": "querying data with LLM", "switched_from": "", "story": "I Still Prefer MCP over Skills"}, {"id": 754389841, "item_id": 47149365, "url": "https://news.ycombinator.com/item?id=47149365", "by": "steinvakt2", "date": "2026-02-25", "stance": "neutral", "quote": "offer alerts and search by indexing it using elasticsearch", "excerpt": "Interesting. Can we get in touch? I just sold my webapp/saas where I used NB-Whisper to transcribe Norwegian media (podcast, radio, TV) and offer alerts and search by indexing it using elasticsearch. Edit: It was https://muninai.eu (I shut down the backend server yesterday so the functionality is disabled).", "context": "sold a SaaS for media transcription and search", "use_case": "indexing transcripts for search", "switched_from": "", "story": "Show HN: Moonshine Open-Weights STT models \u2013 higher accuracy than WhisperLargev3"}, {"id": 750523489, "item_id": 46907718, "url": "https://news.ycombinator.com/item?id=46907718", "by": "tempestn", "date": "2026-02-05", "stance": "recommend", "quote": "found its speed, capabilities, and simplicity all significant improvements compared to the MariaDB-based search", "excerpt": "It really depends on your use case, doesn't it? I'd say, just use Postgres... until you have a reason not to. We used finally switched to Elasticsearch to power user search queries of our vehicle listings a few years ago, and found its speed, capabilities, and simplicity all significant improvements compared to the MariaDB-based search we'd been using previously. (Postgres's search features are likely better than Mar", "context": "runs a vehicle listings product", "use_case": "user search for vehicle listings", "switched_from": "MariaDB", "story": "It's 2026, Just Use Postgres"}, {"id": 746427552, "item_id": 46651722, "url": "https://news.ycombinator.com/item?id=46651722", "by": "aaroninsf", "date": "2026-01-16", "stance": "neutral", "quote": "We use ES like a DB, but, not with SQL; and most importantly, it's not the source of truth/primary store.", "excerpt": "We use ES like a DB, but, not with SQL; and most importantly, it's not the source of truth/primary store. It's operational truth and best-effort.", "context": "", "use_case": "operational data store", "switched_from": "", "story": "Elasticsearch Was Never a Database"}, {"id": 746389136, "item_id": 46649321, "url": "https://news.ycombinator.com/item?id=46649321", "by": "unethical_ban", "date": "2026-01-16", "stance": "warn", "quote": "I would never. Ever. Bet my savings on ES being stable enough to always be online to take in data, or predictable in retaining the data it took in.", "excerpt": "I work in infosec and several popular platforms use elasticsearch for log storage and analysis. I would never. Ever. Bet my savings on ES being stable enough to always be online to take in data, or predictable in retaining the data it took in. It feels very best-effort and as a consultant, I recommend orgs use some other system for retaining their logs, even a raw filesystem with rolling zips, before relying on ES un", "context": "works in infosec as a consultant", "use_case": "log storage and analysis", "switched_from": "", "story": "Elasticsearch Was Never a Database"}, {"id": 742019059, "item_id": 46376191, "url": "https://news.ycombinator.com/item?id=46376191", "by": "1103938364", "date": "2025-12-24", "stance": "recommend", "quote": "L2: Elasticsearch fallback with Painless scripting to score offline users", "excerpt": "Hello HN! I'm the author of SoakUpTheSun. This is an open-source visual assistance platform I built to connect visually impaired users with volunteers via real-time video (similar to \"Be My Eyes\", but open-source). I built this primarily to learn how to handle high-concurrency scenarios and heterogeneous microservices. Key technical implementation details: Custom SFU in Go: Instead of using standard media servers, I ", "context": "", "use_case": "fallback offline user scoring", "switched_from": "", "story": "Show HN: Opensource\"BeMyEyes\"alternative(Java/Go/Python)built as a learning pjet"}, {"id": 732961345, "item_id": 45810084, "url": "https://news.ycombinator.com/item?id=45810084", "by": "inbx0", "date": "2025-11-04", "stance": "compare", "quote": "We have even largely moved away from ElasticSearch to Postgres where we can, because it's just so much easier to implement with new complex filters", "excerpt": "I don't have much experience in dedicated vector databases, I've only used pgvector, so pardon me if there's an obvious answer to this, but how do people do similarity search combined with other filters and pagination with separate vector DB? It's a pretty common use case at least in my circles. For example, give me product listings that match the search term (by vector search), and are made by company X (copanies be", "context": "", "use_case": "search", "switched_from": "", "story": "The Case Against PGVector"}]}