[{"data":1,"prerenderedAt":485},["ShallowReactive",2],{"project-36987920":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":10,"maker":11,"posted_at":12,"year":13,"points":14,"comments":15,"rank_in_year":16,"shown_in_year":17,"top":18,"tier":19,"category":20,"subcategory":21,"format":22,"keywords":23,"reception":28,"sentiment":29,"stance_mix":30,"scored_comments":34,"aspects":35,"strip":46,"post_text":48,"what":49,"said":85,"maker_in_thread":221,"shape":232,"grid":237,"attempts":448,"same_week":449,"maker_shows":41,"maker_hidden":478,"reader_version":479,"card":480},"36987920","Hydra 1.0","open-source column-oriented Postgres","title","Show HN: Hydra 1.0 – open-source column-oriented Postgres","https:\u002F\u002Fhydra-so.notion.site\u002FHydra-1-0-beta-318504444825401e8ce21796dcadd589","hydra-so.notion.site","coatue",1691079547,2023,269,77,179,3109,6,"legend","data","columnar database","other",[24,21,25,26,27],"postgres","analytics","open source","aggregates","curious",0.28,{"positive":31,"neutral":32,"mixed":33,"critical":18},17,24,0,47,{"docs":36,"execution":38,"design":39,"performance":40,"idea":43,"pricing":45},{"positive":37,"critical":37},2,{"positive":33,"critical":33},{"positive":33,"critical":33},{"positive":41,"critical":42},4,1,{"positive":44,"critical":44},3,{"positive":33,"critical":33},[44,44,44,47,33,42,47,44,44,33,33,33,33,33,33,47,44,42,47,47,47,44,33,42,47,44,47,47,44,44,47,47,44,44,33,47,44,47,44,33],5,"hi hn, hydra ceo here\n\nhydra () is an open source, column-oriented postgres. you can set up remarkably fast aggregates on your project in minutes to query billions of rows instantly.\n\npostgres is great, but aggregates can take minutes to hours to return results on large data sets. long-running analytical queries hog database resources and degrade performance. use hydra to run much faster analytics on postgres without making code changes. data is automatically loaded into columnar format and compressed. connect to hydra with your preferred postgres client (psql, dbeaver, etc).\n\nfollowing 4 mont",{"problem":50,"audience":56,"pricing":57,"motivation":61,"time_to_build":56,"stack":65,"openness":82,"stage":83,"team_size":84},{"value":51,"source":52,"evidence":53},"Long-running analytical aggregates on large Postgres datasets are slow and hog resources","maker",[54],{"id":55},"post",null,{"value":58,"source":52,"evidence":59},"Free tier available on cloud",[60],{"id":55},{"value":62,"source":52,"evidence":63},"Make analytics on Postgres much faster without code changes",[64],{"id":55},[66,70],{"value":67,"source":52,"evidence":68},"PostgreSQL",[69],{"id":55},{"value":71,"source":72,"evidence":73},"C","inferred",[74,78],{"id":75,"by":76,"text":77},"36992534","qeternity","Ok so this is a Citus fork. Where can I read about what the differences \u002F trade offs are? I don’t see anything in the docs.",{"id":79,"by":80,"text":81},"36990637","pella","Congratulations! Can we expect support for gist, gin, spgist, and brin indexes sometime in the near future? Based on the source code, it appears that they are not supported:…","open_source","beta","company",{"praise":86,"objections":117,"requests":154,"questions":173,"alternatives":196},[87,99,110],{"value":88,"source":89,"evidence":90},"Fast performance versus Citus and plain Postgres","commenter",[91,95],{"id":92,"by":93,"text":94},"36988628","jerrysievert","generally faster across the board, a lot of work was done to expand and speed it up, plus updates, deletes, and vacuuming.…",{"id":96,"by":97,"text":98},"36988768","mitchpatin","super impressive performance improvements! do most of your customers replicate their postgres database to Hydra for analytics jobs, or what's the typical set up?",{"value":100,"source":89,"evidence":101},"Useful for analytics on Postgres without learning a new database",[102,106],{"id":103,"by":104,"text":105},"36988274","mlenhard","Congrats on the launch! For those who have not experimented with columnar based databases, I would highly recommend toying around with them. The performance improvements can be…",{"id":107,"by":108,"text":109},"36988194","s-mon","This looks wild! Been looking for a good event based logs DB and didn’t want to go full clickhouse. This will do!",{"value":111,"source":89,"evidence":112},"Open source Apache license",[113],{"id":114,"by":115,"text":116},"36988945","mdaniel","I wanted to say thank you for using actual Open Source licenses. It's gotten to where I treat any recent \"Launch HN\" or \"Show HN\" containing \"open source\" in the title as \"well,…",[118,129,144],{"value":119,"source":89,"evidence":120},"Benchmark favors Hydra; plain tuned Postgres wins some queries",[121,125],{"id":122,"by":123,"text":124},"36989458","rubiquity","Since benchmarks can be misleading I want to point out that the differences between Hydra and the \"tuned\"[0] PostgreSQL (which are some very basic settings) are a lot less…",{"id":126,"by":127,"text":128},"36989566","arp242","> plain old PG coming ahead on quite a few I found that is common among these types of databases (e.g. Citus, Timescale, etc.) which perform well under very specific conditions,…",{"value":130,"source":89,"evidence":131},"Documentation lacks migration and extension setup for existing databases",[132,136,140],{"id":133,"by":134,"text":135},"36995034","dikei","For a Postgres extension, there's a strangely lack of documentation on how to add Hydra to an existing PG installation.",{"id":137,"by":138,"text":139},"36992951","ahmedfromtunis","That's also my question. Couldn't find anything for it in the docs provided. Also, how to migrate data from an existing database? (Is it the usual pg_dump\u002Fpsql combo?)",{"id":141,"by":142,"text":143},"36992519","florianherrengt","Can you add the extension to an existing database?",{"value":145,"source":89,"evidence":146},"Licensing confusing since it is a Citus fork under AGPL",[147,151],{"id":148,"by":149,"text":150},"36991076","thih9","Thanks for explaining. This is confusing to me as a github user, i.e. if I saw a license in the project’s description, I wouldn’t expect another license in a subdirectory. Github…",{"id":152,"by":149,"text":153},"36990740","Citus: https:\u002F\u002Fgithub.com\u002Fcitusdata\u002Fcitus BTW, Citus license is GNU Affero General Public License (github lists “conditions: same license”) and hydra is Apache. How is that…",[155,159,163],{"value":156,"source":89,"evidence":157},"Support gist, gin, spgist and brin indexes",[158],{"id":79,"by":80,"text":81},{"value":160,"source":89,"evidence":161},"Document differences from Citus",[162],{"id":75,"by":76,"text":77},{"value":164,"source":89,"evidence":165},"Spatial index support and PostGIS compatibility",[166,169],{"id":167,"by":80,"text":168},"36991842","We need a spatial index for spatial (columnar) data! - https:\u002F\u002Fwww.crunchydata.com\u002Fblog\u002Fthe-many-spatial-indexes-of-postgis -…",{"id":170,"by":171,"text":172},"36995291","mch82","Is hydra compatible with the PostGIS extension?",[174,185,192],{"value":175,"source":89,"evidence":176},"How does it compare to Citus and TimescaleDB",[177,181],{"id":178,"by":179,"text":180},"36988584","therealwardo","how does Hydra compare to Citus? https:\u002F\u002Fwww.citusdata.com",{"id":182,"by":183,"text":184},"36996188","KingOfCoders","How does it compare to Timescaledb? Performance? Features? (TSDB is my current Postgres data lake setup)",{"value":186,"source":89,"evidence":187},"How are updates and deletes handled",[188],{"id":189,"by":190,"text":191},"36992638","quadrature","How are updates handled, is it doing a merge on read ?",{"value":193,"source":89,"evidence":194},"Can the extension be added to an existing database",[195],{"id":141,"by":142,"text":143},[197,202,206,217],{"value":198,"source":89,"evidence":199},"Citus",[200,201],{"id":178,"by":179,"text":180},{"id":75,"by":76,"text":77},{"value":203,"source":89,"evidence":204},"TimescaleDB",[205],{"id":182,"by":183,"text":184},{"value":207,"source":89,"evidence":208},"ClickHouse",[209,213],{"id":210,"by":211,"text":212},"36991320","hodgesrm","Difference principles of indexing, as least based on my experience with ClickHouse. * Column-based stores have really fast scans due to compression and vectorization, so you'll…",{"id":214,"by":215,"text":216},"36992039","riku_iki","it depends on your query obviously. In general, I did very deep benchmarking of pg, clickhouse and duckdb, and I sure didn't make stupid mistakes like this:…",{"value":218,"source":89,"evidence":219},"DuckDB",[220],{"id":214,"by":215,"text":216},{"comments":44,"answered":42,"key":222},[223,226,229],{"id":224,"text":225},"36991235","Nice and thanks @edublancas, that was a useful tutorial and it's nice to be able to query hydra with SQL via Jupyter. fan of your project",{"id":227,"text":228},"36989969","Thanks! feel free to DM me in the hydra discord (or email) anytime",{"id":230,"text":231},"36988691","Check out the \"about us\" section on the page for more details! \"We are excited to share that Hydra raised a $3.1M seed round to drive development of columnar Postgres. We 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