{"slug": "snowflake", "name": "Snowflake", "category": "infra", "category_name": "Infrastructure and DevOps", "description": "", "recommenders": 3, "commenters": 29, "warners": 5, "score": 3.298, "rising": -0.98, "first": "2025-11-14", "latest": "2026-09-24", "why": "We switched to Snowflake, saved money, got better performance, and had a simpler setup.", "why_is_quote": true, "has_verdict": false, "sentiment": {"recommend": 3, "neutral": 19, "compare": 4, "warn": 5}, "spark": [0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0], "listed": true, "loved": [], "caveat": "", "short_quote": "We switched to Snowflake, saved money, got better performance, and had a simpler setup.", "kind": "", "icon": true, "domain": "torproject.org", "github_repo": null, "official_url": "https://www.snowflake.com", "pricing": "", "aliases": ["Snowflake"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 780932992, "item_id": 48808312, "url": "https://news.ycombinator.com/item?id=48808312", "by": "brahmanithota", "date": "2026-07-06", "stance": "recommend", "quote": "I led the migration of enterprise healthcare data off Palantir onto Snowflake", "excerpt": "Location: Columbia, Maryland Remote: Preferred Willing to relocate: Yes Technologies: SQL, Python, PySpark, AWS, Palantir, Snowflake, dbt, Databricks R\u00e9sum\u00e9/CV: https://blue-cloud-565.linkyhost.com Email: thotasadhvika@gmail.com Data Engineer of 5 years of experience with hands-on ownership of financial data infrastructure in high-stakes, regulated environments. At Centene Corporation, I own end-to-end pipelines proc", "context": "Data engineer, 5 years, healthcare financial data", "use_case": "Healthcare data warehouse", "switched_from": "Palantir", "story": "Ask HN: Who wants to be hired? (July 2026)"}, {"id": 769354742, "item_id": 48084671, "url": "https://news.ycombinator.com/item?id=48084671", "by": "nijave", "date": "2026-05-10", "stance": "recommend", "quote": "We switched to Snowflake, saved money, got better performance, and had a simpler setup.", "excerpt": ">AWS IAM is extremely well designed Agree, so is STS and SDKs generally just work. I don't miss on-prem companies with legacy Auth where you maintained 100 service accounts for everything with very careful password vaulting and credentials management policies. So much easier to use IAM policies. >are absolute hot garbage I kind of like Cognito but both Cognito and especially API Gateway are somewhat convoluted to con", "context": "", "use_case": "", "switched_from": "Amazon Redshift", "story": "I returned to AWS, and was reminded why I left"}, {"id": 746704050, "item_id": 46669003, "url": "https://news.ycombinator.com/item?id=46669003", "by": "rawgabbit", "date": "2026-01-18", "stance": "recommend", "quote": "In Snowflake, I use scheduled tasks that call stored procedures.", "excerpt": "Well. I try for a middle ground. I am currently ditching both airflow and dbt. In Snowflake, I use scheduled tasks that call stored procedures. The stored procedures do everything I need to do. I even call external APIs like Datadog\u2019s and Okta\u2019s and pull down the logs directly into snowflake. I do try to name my stored procedures with meaningful names. I also add generous comments including urls back to the original ", "context": "", "use_case": "scheduled stored-procedure pipelines", "switched_from": "", "story": "Command-line Tools can be 235x Faster than your Hadoop Cluster (2014)"}]}], "caveats": [{"label": "", "summary": "", "quotes": [{"id": 788200081, "item_id": 49262505, "url": "https://news.ycombinator.com/item?id=49262505", "by": "wasifaleem", "date": "2026-08-11", "stance": "warn", "quote": "Since Snowflake and Databricks reject equality delete files", "excerpt": "> The issue that each of those providers above has recently adopted Postgres as a secondary product aimed at supporting their main product, an OLAP database or engine, so they don\u2019t want you plugging in your own query engine. Disclosure: I work on Supermetal You don't need to wait for a provider, and the provider is arguably the wrong place for this. They all have an incentive to make their own OLAP engine the happy ", "context": "", "use_case": "", "switched_from": "", "story": "How We Pushed CDC into Postgres"}, {"id": 783020338, "item_id": 48938771, "url": "https://news.ycombinator.com/item?id=48938771", "by": "aleda145", "date": "2026-07-16", "stance": "warn", "quote": "locking themselves into something like Snowflake", "excerpt": "As a data engineering person I can say that this is a great write up! Some thoughts: A \"bubbling\" topic right now is conversational analytics (i.e. talk to your data). There has been an explosion of tools in the last 6 months. YC is backing one too: https://getnao.io/ I feel like pandas is also somewhat frowned upon, the industry has moved on from that. Most SQL tools can now do everything that we could only do with ", "context": "", "use_case": "", "switched_from": "", "story": "Guide to data tools landscape for developers"}, {"id": 763967186, "item_id": 47747949, "url": "https://news.ycombinator.com/item?id=47747949", "by": "horizontech-dev", "date": "2026-04-12", "stance": "warn", "quote": "I was tired of setting up additional read replicas and Snowflake for our BI teams", "excerpt": "I was tired of setting up additional read replicas and Snowflake for our BI teams, I built an analytics database using S3 and DuckDB. https://github.com/viggy28/streambed", "context": "", "use_case": "", "switched_from": "", "story": "Ask HN: What Are You Working On? (April 2026)"}, {"id": 751459872, "item_id": 46966242, "url": "https://news.ycombinator.com/item?id=46966242", "by": "mritchie712", "date": "2026-02-10", "stance": "warn", "quote": "Snowflake charges $3 per compute hour", "excerpt": "> when you connect a warehouse like Snowflake, BigQuery, or Postgres I'm curious what others are seeing connecting AI tools to Snowflake. Snowflake charges $3 per compute hour and it's pretty easy for an agent to run dozens of queries asynchronously. As others have mentioned, if you want a notebook, compare this hard against Hex. It's unclear what LiveDocs would give you over Hex (cheaper maybe?). ps - if you don't h", "context": "", "use_case": "", "switched_from": "", "story": "Launch HN: Livedocs (YC W22) \u2013 An AI-native notebook for data analysis"}]}], "who": [{"by": "brahmanithota", "context": "Data engineer, 5 years, healthcare financial data", "url": "https://news.ycombinator.com/item?id=48808312", "date": "2026-07-06"}, {"by": "getravi", "context": "finance systems and data platform leader, 18+ years, job seeker", "url": "https://news.ycombinator.com/item?id=48755145", "date": "2026-07-01"}, {"by": "arcb", "context": "founder of BitBoard", "url": "https://news.ycombinator.com/item?id=48506800", "date": "2026-06-12"}, {"by": "tjleestjohn", "context": "first author of the paper; team building warehouse-native infrastructure", "url": "https://news.ycombinator.com/item?id=47415349", "date": "2026-03-17"}, {"by": "ksk385", "context": "independent software consultant", "url": "https://news.ycombinator.com/item?id=47224106", "date": "2026-03-02"}, {"by": "throwaw12", "context": "software engineer", "url": "https://news.ycombinator.com/item?id=45924964", "date": "2025-11-14"}], "tags": [], "use_cases": ["healthcare data warehouse", "data warehouse integration", "finance data systems", "enterprise data warehouse", "offline analytics warehouse", "approximate distinct counts in sql"], "compared": [{"slug": "dbt", "name": "dbt", "co": 9, "switched_from": 0, "switched_to": 0}, {"slug": "duckdb", "name": "DuckDB", "co": 7, "switched_from": 0, "switched_to": 0}, {"slug": "postgresql", "name": "PostgreSQL", "co": 5, "switched_from": 0, "switched_to": 0}, {"slug": "react", "name": "React", "co": 5, "switched_from": 0, "switched_to": 0}, {"slug": "clickhouse", "name": "ClickHouse", "co": 4, "switched_from": 0, "switched_to": 0}, {"slug": "amazon-redshift", "name": "Amazon Redshift", "co": 2, "switched_from": 1, "switched_to": 0}], "makers": [{"id": 792454480, "item_id": 49528405, "url": "https://news.ycombinator.com/item?id=49528405", "by": "kendallchuang", "date": "2026-09-01", "stance": "neutral", "quote": "", "excerpt": "Snowflake | Forward Deployed Engineer, Product Manager | Menlo Park, CA | Warsaw, Poland | London, UK | ONSITE I\u2019m part of Snowflake\u2019s Applied AI / Forward Deployed Engineering team, and we\u2019re hiring for multiple roles on the team. We work directly with strategic customers to design, build, deploy, and improve production AI systems on Snowflake. That includes LLM applications, RAG and agentic workflows, evaluation fr", "context": "", "use_case": "Cloud data platform hiring", "switched_from": "", "story": "Ask HN: Who is hiring? (September 2026)"}, {"id": 787886368, "item_id": 49242898, "url": "https://news.ycombinator.com/item?id=49242898", "by": "mslot", "date": "2026-08-10", "stance": "recommend", "quote": "At Snowflake we use Snowflake to do the apply work.", "excerpt": "The challenge is converting primary key updates/deletes to row offsets in a columnar table. That requires maintaining an expensive mapping or doing expensive scans, and is not something you want Postgres itself to do. It's also this bursty, memory-intensive workload that you'd rather not have a lot of dedicated infrastructure for. At Snowflake we use Snowflake to do the apply work. Hence end-to-end mirroring has more", "context": "works at Snowflake, article author", "use_case": "applying Postgres CDC changes", "switched_from": "", "story": "How We Pushed CDC into Postgres"}, {"id": 786613392, "item_id": 49163337, "url": "https://news.ycombinator.com/item?id=49163337", "by": "kendallchuang", "date": "2026-08-03", "stance": "neutral", "quote": "production AI systems on Snowflake", "excerpt": "Snowflake | Forward Deployed Engineer | Menlo Park, CA | ONSITE I\u2019m part of Snowflake\u2019s Applied AI / Forward Deployed Engineering team, and we\u2019re hiring for two roles: Forward Deployed Engineer and Senior Forward Deployed Engineer. We work directly with strategic customers to design, build, deploy, and improve production AI systems on Snowflake. That includes LLM applications, RAG and agentic workflows, evaluation fr", "context": "", "use_case": "Building customer AI systems", "switched_from": "", "story": "Ask HN: Who is hiring? (August 2026)"}, {"id": 773840768, "item_id": 48365048, "url": "https://news.ycombinator.com/item?id=48365048", "by": "kendallchuang", "date": "2026-06-01", "stance": "recommend", "quote": "I\u2019m part of Snowflake\u2019s Applied AI / Forward Deployed Engineering team", "excerpt": "Snowflake | Forward Deployed Engineer | Menlo Park, CA | ONSITE I\u2019m part of Snowflake\u2019s Applied AI / Forward Deployed Engineering team, and we\u2019re hiring for two roles: Forward Deployed Engineer and Senior Forward Deployed Engineer. We work directly with strategic customers to design, build, deploy, and improve production AI systems on Snowflake. That includes LLM applications, RAG and agentic workflows, evaluation fr", "context": "Part of Snowflake's Applied AI / Forward Deployed Engineering team", "use_case": "", "switched_from": "", "story": "Ask HN: Who is hiring? (June 2026)"}, {"id": 759105392, "item_id": 47444087, "url": "https://news.ycombinator.com/item?id=47444087", "by": "iamonthesnow", "date": "2026-03-19", "stance": "neutral", "quote": "the fix implemented/deployed by our security team", "excerpt": "Hi folks, I am a Snowflake Employee and just wanted to share (as FYI) the timeline on discovery, validation, and the fix implemented/deployed by our security team. For those interested, here's the link to the detailed article: https://community.snowflake.com/s/article/PromptArmor-Report---Snowflake-Response", "context": "Snowflake employee", "use_case": "", "switched_from": "", "story": "Snowflake AI Escapes Sandbox and Executes Malware"}], "threads": [{"url": "https://news.ycombinator.com/item?id=49238050", "title": "How We Pushed CDC into Postgres", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=48747975", "title": "Ask HN: Who wants to be hired? (July 2026)", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=46761822", "title": "Iran's internet blackout may become permanent, with access for elites only", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=45920881", "title": "650GB of Data (Delta Lake on S3). Polars vs. DuckDB vs. Daft vs. Spark", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=49835815", "title": "GizmoSQL changes the unit economics for AI analyst companies", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49522897", "title": "Ask HN: Who is hiring? (September 2026)", "mentions": 1}], "sentiment_by_month": {"2025-11": {"neutral": 2}, "2025-12": {"neutral": 1}, "2026-01": {"recommend": 1, "warn": 2, "neutral": 2, "compare": 1}, "2026-02": {"neutral": 6, "compare": 1}, "2026-03": {"neutral": 3}, "2026-04": {"warn": 1}, "2026-05": {"neutral": 2, "recommend": 1}, "2026-06": {"neutral": 2, "compare": 1}, "2026-07": {"neutral": 1, "recommend": 1, "warn": 1}, "2026-08": {"warn": 1}, "2026-09": {"compare": 1}, "2026-10": {}}, "quotes": [{"id": 797373057, "item_id": 49835816, "url": "https://news.ycombinator.com/item?id=49835816", "by": "emms21", "date": "2026-09-24", "stance": "compare", "quote": "Snowflake's cache is a cost saver", "excerpt": "Self-service AI analytics products turn a question into SQL and run it against their customers' data warehouse to derive insights for their dashboards. Snowflake's cache is a cost saver if the dashboard runs the same SQL again and the underlying data has not changed. GizmoSQL would take the rows from that first query and hold them in DuckDB temporarily. Subsequent questions on the dashboard would save over 50% of the", "context": "", "use_case": "", "switched_from": "", "story": "GizmoSQL changes the unit economics for AI analyst companies"}, {"id": 788200081, "item_id": 49262505, "url": "https://news.ycombinator.com/item?id=49262505", "by": "wasifaleem", "date": "2026-08-11", "stance": "warn", "quote": "Since Snowflake and Databricks reject equality delete files", "excerpt": "> The issue that each of those providers above has recently adopted Postgres as a secondary product aimed at supporting their main product, an OLAP database or engine, so they don\u2019t want you plugging in your own query engine. Disclosure: I work on Supermetal You don't need to wait for a provider, and the provider is arguably the wrong place for this. They all have an incentive to make their own OLAP engine the happy ", "context": "", "use_case": "", "switched_from": "", "story": "How We Pushed CDC into Postgres"}, {"id": 783020338, "item_id": 48938771, "url": "https://news.ycombinator.com/item?id=48938771", "by": "aleda145", "date": "2026-07-16", "stance": "warn", "quote": "locking themselves into something like Snowflake", "excerpt": "As a data engineering person I can say that this is a great write up! Some thoughts: A \"bubbling\" topic right now is conversational analytics (i.e. talk to your data). There has been an explosion of tools in the last 6 months. YC is backing one too: https://getnao.io/ I feel like pandas is also somewhat frowned upon, the industry has moved on from that. Most SQL tools can now do everything that we could only do with ", "context": "", "use_case": "", "switched_from": "", "story": "Guide to data tools landscape for developers"}, {"id": 780932992, "item_id": 48808312, "url": "https://news.ycombinator.com/item?id=48808312", "by": "brahmanithota", "date": "2026-07-06", "stance": "recommend", "quote": "I led the migration of enterprise healthcare data off Palantir onto Snowflake", "excerpt": "Location: Columbia, Maryland Remote: Preferred Willing to relocate: Yes Technologies: SQL, Python, PySpark, AWS, Palantir, Snowflake, dbt, Databricks R\u00e9sum\u00e9/CV: https://blue-cloud-565.linkyhost.com Email: thotasadhvika@gmail.com Data Engineer of 5 years of experience with hands-on ownership of financial data infrastructure in high-stakes, regulated environments. At Centene Corporation, I own end-to-end pipelines proc", "context": "Data engineer, 5 years, healthcare financial data", "use_case": "Healthcare data warehouse", "switched_from": "Palantir", "story": "Ask HN: Who wants to be hired? (July 2026)"}, {"id": 780082321, "item_id": 48755145, "url": "https://news.ycombinator.com/item?id=48755145", "by": "getravi", "date": "2026-07-01", "stance": "neutral", "quote": "built planning/data pipelines with Snowflake", "excerpt": "Location: SF Bay Area Remote: Yes, also open to hybrid or onsite in the Bay Area Willing to relocate: No, but open to Bay Area onsite roles Technologies: Python, SQL, TypeScript/React, Node.js, PostgreSQL, Snowflake, dbt, Airflow, APIs, Anaplan, NetSuite, Workday, Salesforce, Tableau, Power BI, Microsoft Power Apps, Claude Code, Codex, Hermes Agent, Vercel v0 R\u00e9sum\u00e9/CV: https://www.linkedin.com/in/getravi/ Email: get", "context": "finance systems and data platform leader, 18+ years, job seeker", "use_case": "", "switched_from": "", "story": "Ask HN: Who wants to be hired? (July 2026)"}, {"id": 777160624, "item_id": 48572539, "url": "https://news.ycombinator.com/item?id=48572539", "by": "diebillionaires", "date": "2026-06-17", "stance": "neutral", "quote": "But mostly Snowflake or AWS.", "excerpt": "This was covered in NOH's data broker article. But mostly Snowflake or AWS. https://nooneshappy.com/article/data-brokers-unregulated-forensic-analysis/", "context": "", "use_case": "", "switched_from": "", "story": "ICE Appears to Be Buying Immigrants' Tax Identifiers from a Data Broker"}, {"id": 776676561, "item_id": 48542285, "url": "https://news.ycombinator.com/item?id=48542285", "by": "anentropic", "date": "2026-06-15", "stance": "compare", "quote": "basically a clone of Snowflake's semantic views but for DuckDB", "excerpt": "Various stuff around Semantic Views for data warehouse / analytics Starting with https://anentropic.github.io/duckdb-semantic-views/ which is basically a clone of Snowflake's semantic views but for DuckDB (see also Databricks Metric Views)", "context": "", "use_case": "", "switched_from": "", "story": "Ask HN: What are you working on? (June 2026)"}, {"id": 776108801, "item_id": 48506800, "url": "https://news.ycombinator.com/item?id=48506800", "by": "arcb", "date": "2026-06-12", "stance": "neutral", "quote": "we do work with Snowflake (and Databricks and other warehouses) as well", "excerpt": "Our outreach is vertical-specific, and healthcare is indeed on the list! But what we learned working a vertical is that the primitives underneath (shared queries, permissions, caching, refresh semantics) repeat across industries. We use DuckDB internally because we like its ergonomics - it's flexible, runs well in memory, manages a lot of file structures under the hood, but we do work with Snowflake (and Databricks a", "context": "founder of BitBoard", "use_case": "data warehouse integration", "switched_from": "", "story": "Launch HN: BitBoard (YC P25) \u2013 Analytics Workspace for Agents"}, {"id": 769354742, "item_id": 48084671, "url": "https://news.ycombinator.com/item?id=48084671", "by": "nijave", "date": "2026-05-10", "stance": "recommend", "quote": "We switched to Snowflake, saved money, got better performance, and had a simpler setup.", "excerpt": ">AWS IAM is extremely well designed Agree, so is STS and SDKs generally just work. I don't miss on-prem companies with legacy Auth where you maintained 100 service accounts for everything with very careful password vaulting and credentials management policies. So much easier to use IAM policies. >are absolute hot garbage I kind of like Cognito but both Cognito and especially API Gateway are somewhat convoluted to con", "context": "", "use_case": "", "switched_from": "Amazon Redshift", "story": "I returned to AWS, and was reminded why I left"}, {"id": 768455952, "item_id": 48028497, "url": "https://news.ycombinator.com/item?id=48028497", "by": "getravi", "date": "2026-05-05", "stance": "neutral", "quote": "using Python, SQL, Snowflake/dbt/Airflow, and Anaplan", "excerpt": "Location: San Francisco Bay Area Remote:Yes Willing to relocate: Yes Technologies: R\u00e9sum\u00e9/CV: https://www.linkedin.com/in/getravi (happy to send you a pdf over email) Email: getravi at gmail Tech-forward finance systems / data engineer (18+ yrs) at the intersection of FP&A, data infra, and internal tooling (currently at eBay; previously Sonder, Adobe). I build systems that replace spreadsheet-heavy workflows using Py", "context": "finance systems / data engineer, 18+ years", "use_case": "finance data systems", "switched_from": "", "story": "Ask HN: Who wants to be hired? (May 2026)"}, {"id": 767627985, "item_id": 47976749, "url": "https://news.ycombinator.com/item?id=47976749", "by": "safoor", "date": "2026-05-01", "stance": "neutral", "quote": "companies scaling on Kubernetes and Snowflake", "excerpt": "EaseCloud | Remote (EST overlap) | Full-Time | Platform & Data Engineers | https://www.easecloud.io EaseCloud builds cloud platforms and modern data stacks for companies scaling on Kubernetes and Snowflake. We\u2019re hiring engineers who like working across infra + data and actually running what they build in production. Open Roles: ++ Platform Engineer (Python, GCP & Azure) [Kubernetes, Terraform, Python, GCP, Azure, CI", "context": "", "use_case": "", "switched_from": "", "story": "Ask HN: Who is hiring? (May 2026)"}, {"id": 763967186, "item_id": 47747949, "url": "https://news.ycombinator.com/item?id=47747949", "by": "horizontech-dev", "date": "2026-04-12", "stance": "warn", "quote": "I was tired of setting up additional read replicas and Snowflake for our BI teams", "excerpt": "I was tired of setting up additional read replicas and Snowflake for our BI teams, I built an analytics database using S3 and DuckDB. https://github.com/viggy28/streambed", "context": "", "use_case": "", "switched_from": "", "story": "Ask HN: What Are You Working On? (April 2026)"}, {"id": 758645584, "item_id": 47415349, "url": "https://news.ycombinator.com/item?id=47415349", "by": "tjleestjohn", "date": "2026-03-17", "stance": "neutral", "quote": "warehouse-native infrastructure (Snowflake, Databricks, etc.)", "excerpt": "Hello HN, I'm Terry, the first author. I spent the last 2.5+ years formalizing this theory to explain a strange anomaly I kept encountering in industry: models trained on vast, incredibly dirty, uncurated datasets were sometimes achieving state-of-the-art predictive performance, completely defying the \"Garbage In, Garbage Out\" mantra. The TL;DR of the paper [https://arxiv.org/abs/2603.12288] is a formal mathematical ", "context": "first author of the paper; team building warehouse-native infrastructure", "use_case": "Enterprise data warehouse", "switched_from": "", "story": "Show HN: A mathematical proof that more dirty features can beat fewer clean ones"}, {"id": 757980450, "item_id": 47373778, "url": "https://news.ycombinator.com/item?id=47373778", "by": "shahar_biron", "date": "2026-03-13", "stance": "neutral", "quote": "", "excerpt": "Apart from working within the Snowflake ecosystem, you can also manage FalkorDB outside of Snowflake and still have your data up to date, using the CDC tool we've created: https://github.com/FalkorDB/DM-SQL-to-FalkorDB", "context": "", "use_case": "", "switched_from": "", "story": "Native Graph Queries on Snowflake"}, {"id": 755585697, "item_id": 47224106, "url": "https://news.ycombinator.com/item?id=47224106", "by": "ksk385", "date": "2026-03-02", "stance": "neutral", "quote": "Data: Databricks, Snowflake, dbt, DuckDB, Tuva Data Model", "excerpt": "Location: Greater New York Area Remote: Yes (US-based) Willing to relocate: No Services: Healthcare data engineering, Clinical data pipelines, AI/ML integrations, Cloud architecture, Full-stack development, Technical Discovery About Me: I'm Karan Krishnani, an independent software consultant with almost 20 years of experience. For the last several years I've been focused on healthcare tech, building HIPAA-compliant d", "context": "independent software consultant", "use_case": "", "switched_from": "", "story": "Ask HN: Who wants to be hired? (March 2026)"}, {"id": 754120816, "item_id": 47132551, "url": "https://news.ycombinator.com/item?id=47132551", "by": "levkk", "date": "2026-02-23", "stance": "neutral", "quote": "It worked well, but Snowflake was only usable for offline analytics", "excerpt": "A couple options come to mind: 1. Replicate shards into one beefy database and use that. Replication is cheaper than individual statements, so this can work for a while. The sink can be Postgres or another database like Clickhouse. At Instacart, we used Snowflake, with an in-house CDC pipeline. It worked well, but Snowflake was only usable for offline analytics, like BI / batch ML, and quite expensive. We'll add supp", "context": "", "use_case": "offline analytics warehouse", "switched_from": "", "story": "Show HN: PgDog \u2013 scale Postgres without changing the app"}, {"id": 753737520, "item_id": 47108595, "url": "https://news.ycombinator.com/item?id=47108595", "by": "benmanns", "date": "2026-02-21", "stance": "neutral", "quote": "I occasionally use things like APPROX_COUNT_DISTINCT in Snowflake", "excerpt": "They were only touched on (and just barely) in my CS education, so don\u2019t feel too left out. Spend an evening or two on the Wiki for Probabilistic data structures[0]. With a CS education you should have the baseline knowledge to find them really fascinating. Enjoy! Oh, and I don\u2019t find myself actually implementing any of these very often or knowing that they are in use. I occasionally use things like APPROX_COUNT_DIST", "context": "", "use_case": "Approximate distinct counts in SQL", "switched_from": "", "story": "Two Bits Are Better Than One: making bloom filters 2x more accurate"}, {"id": 751647331, "item_id": 46977958, "url": "https://news.ycombinator.com/item?id=46977958", "by": "btcalex", "date": "2026-02-11", "stance": "neutral", "quote": "experience in dbt/snowflake/postgres", "excerpt": "SEEKING WORK | Chicago | Remote I'm a backend engineer primarily (python, node/typescript) with experience as a full stack freelancer (react) and as a data engineer (experience in dbt/snowflake/postgres). I am looking for short term contracts with 10 or less billable hours which I can complete before the end of February. My usual rate is $100 an hour. If you have bugs or features in your backlog which are constantly ", "context": "", "use_case": "", "switched_from": "", "story": "Ask HN: Freelancer? Seeking freelancer? (February 2026)"}, {"id": 751459872, "item_id": 46966242, "url": "https://news.ycombinator.com/item?id=46966242", "by": "mritchie712", "date": "2026-02-10", "stance": "warn", "quote": "Snowflake charges $3 per compute hour", "excerpt": "> when you connect a warehouse like Snowflake, BigQuery, or Postgres I'm curious what others are seeing connecting AI tools to Snowflake. Snowflake charges $3 per compute hour and it's pretty easy for an agent to run dozens of queries asynchronously. As others have mentioned, if you want a notebook, compare this hard against Hex. It's unclear what LiveDocs would give you over Hex (cheaper maybe?). ps - if you don't h", "context": "", "use_case": "", "switched_from": "", "story": "Launch HN: Livedocs (YC W22) \u2013 An AI-native notebook for data analysis"}, {"id": 750275537, "item_id": 46892221, "url": "https://news.ycombinator.com/item?id=46892221", "by": "mritchie712", "date": "2026-02-04", "stance": "neutral", "quote": "Snowflake is starting down this direction", "excerpt": "also, who pays for \"a data visualization\" SaaS? I guess they mean BI, but for a company of any scale, they aren't paying for a chart, they're paying for a permissions system, query caching, a modeling layer, scheduling, export to excel, etc. Stand alone BI tools are going to struggle, but not because they can easily be vibe coded. It'll be because data platforms have BI built-in. Snowflake is starting down this direc", "context": "", "use_case": "", "switched_from": "", "story": "AI Is Killing B2B SaaS"}, {"id": 750209045, "item_id": 46888065, "url": "https://news.ycombinator.com/item?id=46888065", "by": "dashdoesdata", "date": "2026-02-04", "stance": "compare", "quote": "Exasol (and SingleStore, Snowflake, BigQuery, etc) are more focused on enterprise BI", "excerpt": "You need to look at use-case alignment as well as performance. Apache Pinot, Druid and Clickhouse are designed for low-latency analytical queries at high concurrency with continuous ingestion. Pinot is popular because of it's native integration with streaming systems like Kafka, varied indexing, and it's ability to scale efficiently. They're widely used in observability and user-facing analytics \u2013 which are how \u201creal", "context": "", "use_case": "", "switched_from": "", "story": "Database Benchmarks Lie (If You Let Them)"}, {"id": 749990470, "item_id": 46874404, "url": "https://news.ycombinator.com/item?id=46874404", "by": "whatrocks", "date": "2026-02-03", "stance": "neutral", "quote": "Tech Stack: Rails, React, TypeScript, PostgreSQL, AWS, Elasticsearch, DBT, Snowflake", "excerpt": "Folio | Backend / Product Engineers | REMOTE (US) | Full-time | https://folio.co Hotel procurement's a $400B industry still running on spreadsheets and phone calls (and faxes!). We're bringing world-class AI search, web automations, and payment infra to this massive space. Folio is a first-of-its-kind marketplace connecting hotels + restaurants with their hundreds of suppliers using our AI-driven concierge-buying, in", "context": "", "use_case": "", "switched_from": "", "story": "Ask HN: Who is hiring? (February 2026)"}, {"id": 749837209, "item_id": 46864825, "url": "https://news.ycombinator.com/item?id=46864825", "by": "straydusk", "date": "2026-02-02", "stance": "neutral", "quote": "Snowflake", "excerpt": "Location: Seattle Remote: Prefer hybrid, remote for the right oppportunity Willing to relocate: No Technologies: SQL, A/B Testing, TypeScript, JS, Python, SQL, R, Next.js, React, A/B Testing, CI/CD, LLM Integration (OpenAI, Anthropic Claude), Vercel AI SDK, Prompt Engineering, AI-Assisted Development (Claude Code, Cursor), ML Enablement, Platform & Infrastructure (event pipelines, data lakes, warehousing), Governance", "context": "", "use_case": "", "switched_from": "", "story": "Ask HN: Who wants to be hired? (February 2026)"}, {"id": 749055681, "item_id": 46815980, "url": "https://news.ycombinator.com/item?id=46815980", "by": "mritchie712", "date": "2026-01-29", "stance": "warn", "quote": "can only write SQL in Snowflake", "excerpt": "Piling on to the vendor pitches here: We give you all of this in 5 minutes at https://www.definite.app/. And I mean all of it. You don't need Spark or Snowflake. We give you a datalake, pipelines to get data in, semantic layer and a data agent in one app. The agent is kind of the easy / fun part. Getting the data infrastructure right so the agent is useful is the hard part. i.e. if the agent has low agency (e.g. can ", "context": "", "use_case": "", "switched_from": "", "story": "OpenAI's In-House Data Agent"}, {"id": 748433328, "item_id": 46777083, "url": "https://news.ycombinator.com/item?id=46777083", "by": "siev", "date": "2026-01-27", "stance": "neutral", "quote": "", "excerpt": "I usually use snowflake as a last resort, and even that's not consistently working right now. However I've seen people recommend running Conduit[1] to friends overseas, which is an easy-to-use Psiphon proxy node. Psiphon is a popular circumvention tool here so that could be helpful. [1] https://conduit.psiphon.ca/", "context": "", "use_case": "", "switched_from": "", "story": "Iran's internet blackout may become permanent, with access for elites only"}, {"id": 748323621, "item_id": 46770226, "url": "https://news.ycombinator.com/item?id=46770226", "by": "saisrirampur", "date": "2026-01-26", "stance": "compare", "quote": "Compared to Snowflake and Databricks", "excerpt": "Thanks for posting this question! Compared to Snowflake and Databricks, a few key differences in our approach are: (a) An initial focus on real-time, customer-facing applications rather than trying to boil the ocean. This also aligns with where the Postgres + ClickHouse combination has really shined for our users. Both Postgres and ClickHouse are designed primarily with developers building their system of record appl", "context": "", "use_case": "", "switched_from": "", "story": "Show HN: Postgres and ClickHouse as a unified data stack"}, {"id": 748212704, "item_id": 46763294, "url": "https://news.ycombinator.com/item?id=46763294", "by": "_ink_", "date": "2026-01-26", "stance": "neutral", "quote": "are the people relying on https://snowflake.torproject.org/ and adding bandwidth there actually makes a difference?", "excerpt": "I there anything the outside world can do? Like are the people relying on https://snowflake.torproject.org/ and adding bandwidth there actually makes a difference?", "context": "", "use_case": "censorship circumvention", "switched_from": "", "story": "Iran's internet blackout may become permanent, with access for elites only"}, {"id": 747848656, "item_id": 46740541, "url": "https://news.ycombinator.com/item?id=46740541", "by": "tison", "date": "2026-01-23", "stance": "warn", "quote": "Snowflake doesn't have adaptive indexes, and its performance would be significantly degraded as data grows", "excerpt": "We have discussed these in previous blogs: 1. Insight In No Time: https://www.scopedb.io/blog/insight-in-no-time 2. Manage Data in Petabytes for an Observability Platform: https://www.scopedb.io/blog/manage-observability-data-in-petabytes That is, Snowflake follows a traditional data warehouse workflow that requires extenral ETL process to load data into the warehouse. Some of our customers did researching of Snowfla", "context": "", "use_case": "cloud data warehouse", "switched_from": "", "story": "A cloud-native database should be as elastic as the cloud itself"}, {"id": 746704050, "item_id": 46669003, "url": "https://news.ycombinator.com/item?id=46669003", "by": "rawgabbit", "date": "2026-01-18", "stance": "recommend", "quote": "In Snowflake, I use scheduled tasks that call stored procedures.", "excerpt": "Well. I try for a middle ground. I am currently ditching both airflow and dbt. In Snowflake, I use scheduled tasks that call stored procedures. The stored procedures do everything I need to do. I even call external APIs like Datadog\u2019s and Okta\u2019s and pull down the logs directly into snowflake. I do try to name my stored procedures with meaningful names. I also add generous comments including urls back to the original ", "context": "", "use_case": "scheduled stored-procedure pipelines", "switched_from": "", "story": "Command-line Tools can be 235x Faster than your Hadoop Cluster (2014)"}, {"id": 741414149, "item_id": 46338384, "url": "https://news.ycombinator.com/item?id=46338384", "by": "dukeyukey", "date": "2025-12-20", "stance": "neutral", "quote": "all of ours logs to Datadog, Sentry, Snowflake", "excerpt": "We use AWS Bedrock, so everything stays within our AWS account. It's not like we aren't already uploading our code to GitHub for version control, AWS for deployment, Jetbrains for development, all of ours logs to Datadog, Sentry, Snowflake, and more.", "context": "", "use_case": "", "switched_from": "", "story": "LLM Year in Review"}, {"id": 734801458, "item_id": 45925091, "url": "https://news.ycombinator.com/item?id=45925091", "by": "roeja", "date": "2025-11-14", "stance": "neutral", "quote": "Snowflake has their own sql engine and is more of a serverless option.", "excerpt": "Snowflake has their own sql engine and is more of a serverless option. Databricks started off with spark but now also has a sql engine(optional serverless) as well, they are using spark in the article. The delta format is Databricks lakehouse file format, snowflake uses iceberg I believe. Both Snowflake and Databricks also provide a ton of other features like ML, Orchestration and governance. Motherduck would be the ", "context": "", "use_case": "", "switched_from": "", "story": "650GB of Data (Delta Lake on S3). Polars vs. DuckDB vs. Daft vs. Spark"}, {"id": 734799424, "item_id": 45924964, "url": "https://news.ycombinator.com/item?id=45924964", "by": "throwaw12", "date": "2025-11-14", "stance": "neutral", "quote": "we use Snowflake", "excerpt": "I am curious as well about this, we use Snowflake, but as a software engineer I want to understand how Spark/Databricks is different, what are we missing out? How we work with data is simple, if SQL+dashboard solves the problem then we do it in Snowflake, if we need something more advanced, then code + bunch of SQL. Pretty sure ML engineers work in different ways, but I don't know that side well", "context": "software engineer", "use_case": "", "switched_from": "", "story": "650GB of Data (Delta Lake on S3). Polars vs. DuckDB vs. Daft vs. Spark"}]}