[{"data":1,"prerenderedAt":483},["ShallowReactive",2],{"project-23616878":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":29,"sentiment":30,"stance_mix":31,"scored_comments":35,"aspects":36,"strip":45,"post_text":48,"what":49,"said":80,"maker_in_thread":203,"shape":211,"grid":214,"attempts":446,"same_week":447,"maker_shows":42,"maker_hidden":476,"reader_version":477,"card":478},"23616878","QuestDB","Query 1.6B rows in milliseconds, live","title","Show HN: Query 1.6B rows in milliseconds, live","http:\u002F\u002Ftry.questdb.io:9000\u002Findex.html","try.questdb.io","bluestreak",1592932082,2020,271,93,161,3028,6,"legend","data","time-series database","web_app",[24,25,26,27,28],"time series database","column store","sql database","swisstable hash","clickhouse alternative","curious",-0.25,{"positive":18,"neutral":32,"mixed":33,"critical":34},41,1,14,62,{"idea":37,"performance":39,"design":41,"execution":44},{"positive":38,"critical":33},0,{"positive":33,"critical":40},9,{"positive":42,"critical":43},3,4,{"positive":38,"critical":38},[42,42,42,42,33,42,42,42,38,38,38,42,42,42,33,42,42,42,33,42,42,46,47,42,42,33,42,42,47,47,42,33,38,33,33,42,46,33,47,42],2,5,null,{"problem":50,"audience":48,"pricing":48,"motivation":61,"time_to_build":48,"stack":65,"openness":77,"stage":78,"team_size":79},{"value":51,"source":52,"evidence":53},"Running fast SQL aggregations over very large time-series datasets on a single node.","maker",[54,57],{"id":55,"by":11,"text":56},"23616896","Author here. A few weeks ago, we wrote about how we implemented SIMD instructions to aggregate a billion rows in milliseconds [1] thanks in great part to Agner Fog’s VCL library…",{"id":58,"by":59,"text":60},"23619555","sa46","How timely! I've done a deep dive into column store databases for the past couple of weeks. Reading through the Quest docs, I'd give it the following characteristics. Are these…",{"value":62,"source":52,"evidence":63},"Showcase the latest release's performance on keyed aggregations.",[64],{"id":55,"by":11,"text":56},[66,73],{"value":67,"source":52,"evidence":68},"Java",[69,70],{"id":55,"by":11,"text":56},{"id":71,"by":11,"text":72},"23618825","Our startup sequence is sub-optimal. We query JDK to index timezone database and JDK generates a tonne of garbage in the process. The whole feat requires roughly 500MB RAM. Once…",{"value":74,"source":52,"evidence":75},"C++",[76],{"id":55,"by":11,"text":56},"open_source","launched","unknown",{"praise":81,"objections":94,"requests":132,"questions":155,"alternatives":179},[82],{"value":83,"source":84,"evidence":85},"Impressive performance on simple queries.","commenter",[86,90],{"id":87,"by":88,"text":89},"23623350","calibas","I abused LEFT JOIN to create a query that produces 224,964,999,650,251 rows. Only 3.68ms execution time, now that's impressive!",{"id":91,"by":92,"text":93},"23621784","strikelaserclaw","Very impressive, i think building your own (performant) database from scratch is one of the most impressive software engineering feats. Can you let me know a little bit of how an…",[95,114,125],{"value":96,"source":84,"evidence":97},"Many common queries take tens of seconds to minutes; WHERE and GROUP BY paths are not yet optimised.",[98,102,106,110],{"id":99,"by":100,"text":101},"23628369","valyala","Great demo! I'm curios why the following query doesn't finish in tens of seconds: ``` select sum(passenger_count) from trips where passenger_count=1 ``` The same query is…",{"id":103,"by":104,"text":105},"23620877","gubby","FYI, this query took 81 seconds: select count(*) from trips where fare_amount > 0 Presumably this is Hacker News load?",{"id":107,"by":108,"text":109},"23619385","lykr0n","`select distinct pickup_latitude, count(*) from trips` takes 241.37s. But some of the more top level queries are quite fast.",{"id":111,"by":112,"text":113},"23706149","keshavmr","SELECT vendor_id, cab_type, avg(fare_amount) from trips; This takes ~86 seconds. Ran it multiple times. SIMD is one of the ingredients for better query performance, but NOT THE…",{"value":115,"source":84,"evidence":116},"Back button is hijacked by the demo page.",[117,121],{"id":118,"by":119,"text":120},"23620608","LordOfWolves","How nice of you to hijack the back-button (to return to HN after some sample queries) despite that being how myself & others found this in the first place. I was really liking…",{"id":122,"by":123,"text":124},"23619206","woodgrainz","I don't know anything about this database, but this link did break the browser \u003Cback> button. Perhaps you can look into fixing that in a future release.",{"value":126,"source":84,"evidence":127},"Few aggregation functions compared to ClickHouse.",[128],{"id":129,"by":130,"text":131},"23639284","pachico","It looks very proming, congrats. I use ClickHouse in production and I'd love to see how this project evolves. My main disappointment is the amount of aggregation functions:…",[133,140,147],{"value":134,"source":84,"evidence":135},"Add GROUP BY and EXPLAIN support.",[136],{"id":137,"by":138,"text":139},"23620593","twoodfin","Very cool. Major props for putting this out there and accepting arbitrary queries. Couple comments \u002F questions: - Correct that there’s no GROUP BY support? - EXPLAIN or similar…",{"value":141,"source":84,"evidence":142},"Support out-of-order inserts.",[143],{"id":144,"by":145,"text":146},"23625770","maltalex","That's a very cool demo, good job! I have a few questions if you don't mind. - Could you share the specs of the hardware powering the demo? - For IoT-type usage, one common…",{"value":148,"source":84,"evidence":149},"Add geo support and compression.",[150,154],{"id":151,"by":152,"text":153},"23620210","Bedon292","Any plans for geo support? Looks like you have lat\u002Flon stored as two independent doubles, which does not lend itself well to any sort of geo operations.",{"id":144,"by":145,"text":146},[156,168],{"value":157,"source":84,"evidence":158},"How does it compare to ClickHouse, TimescaleDB, Druid or Pinot?",[159,163,167],{"id":160,"by":161,"text":162},"23618740","tpayet","Cool project :) How would you compare QuestDB against TimescaleDB?",{"id":164,"by":165,"text":166},"23624652","patelh","Any comparisons to Druid or Pinot?",{"id":55,"by":11,"text":56},{"value":169,"source":84,"evidence":170},"What are the hardware specs and minimum RAM?",[171,175],{"id":172,"by":173,"text":174},"23621372","yumraj","A peek into the hardware specs behind this: CPU, memory, storage, network would be nice.",{"id":176,"by":177,"text":178},"23618678","lux","I was looking for dev\u002Fproduction specs for QuestDB the other day and didn't see them in the docs. Being that it's in Java, which can be quite memory-hungry, what's the minimum…",[180,185,190,197],{"value":181,"source":84,"evidence":182},"ClickHouse",[183,184],{"id":58,"by":59,"text":60},{"id":99,"by":100,"text":101},{"value":186,"source":84,"evidence":187},"TimescaleDB",[188,189],{"id":58,"by":59,"text":60},{"id":144,"by":145,"text":146},{"value":191,"source":84,"evidence":192},"VictoriaMetrics",[193],{"id":194,"by":195,"text":196},"23624343","gregwebs","This seems very similar to Victoria Metrics. Victoria Metrics is very much based on the design of Clickhouse and currently shows best of class performance numbers for time series…",{"value":198,"source":52,"evidence":199},"Athena",[200],{"id":201,"by":11,"text":202},"23617225","Athena has been benchmaked here with similar dataset (1.1B vs our 1.6Bn): https:\u002F\u002Ftech.marksblogg.com\u002Fbenchmarks.html",{"comments":204,"answered":40,"key":205},19,[206,207,208],{"id":55,"text":56},{"id":201,"text":202},{"id":209,"text":210},"23629288","the use of where clause right now turns off vectorization completely is falls back on simple single threaded execution. This is the reason why the query is slow right now. We are…",{"commenters":212,"max_depth":47,"maker_replies":204,"first_comment_mins":33,"lifespan_hours":213},49,195,[215,217,221,222,226,229,232,235,237,241,243,245,246,248,250,253,255,257,261,263,266,269,273,275,278,281,282,284,287,288,291,293,295,296,299,301,303,304,307,309,311,313,315,317,319,321,323,325,328,331,333,337,339,340,342,346,348,350,352,355,359,362,364,366,368,370,374,377,379,381,386,389,393,395,398,401,403,406,408,411,414,416,419,422,424,426,428,431,433,436,439,441,443],[55,38,38,216,11,33],"maker\u002Fneutral\u002Fperformance",[218,38,42,219,220,38],"23617196","maker\u002Fneutral\u002Fidea","osipov",[201,38,38,216,11,33],[223,38,42,224,225,38],"23617568","project\u002Fneutral\u002Fidea","TheTank",[227,38,42,224,228,38],"23625404","seektable",[230,38,42,224,231,38],"23626397","y42",[233,38,38,234,228,38],"23626526","commenter\u002Fneutral\u002Fnone",[144,38,42,236,145,38],"maker\u002Fneutral\u002Fnone",[238,38,42,239,240,38],"23626435","project\u002Fneutral\u002Fnone","sirffuzzylogik",[99,38,33,242,100,38],"project\u002Fcritical\u002Fperformance",[209,38,38,244,11,33],"project\u002Fneutral\u002Fperformance",[58,33,42,224,59,38],[247,33,38,239,11,33],"23619690",[249,33,42,244,59,38],"23619788",[251,33,38,252,11,33],"23619881","project\u002Fneutral\u002Fdesign",[254,33,42,252,225,38],"23620005",[256,33,42,252,228,38],"23625027",[258,33,38,259,260,38],"23621954","other\u002Fneutral\u002Fperformance","dvasdekis",[262,33,38,244,11,33],"23622822",[264,33,38,259,265,38],"23629821","spacentropy",[267,33,38,268,59,38],"23631738","other\u002Fneutral\u002Fnone",[270,46,38,271,272,38],"23619121","other\u002Fneutral\u002Fidea","dvnguyen",[274,46,38,271,123,38],"23621152",[276,46,38,271,277,38],"23622249","dls2016",[279,46,38,271,280,38],"23623243","ramraj07",[137,42,42,239,138,38],[283,42,38,239,11,33],"23620673",[285,42,42,239,286,38],"23620773","rzzzt",[87,43,42,244,88,38],[289,43,42,244,290,38],"23626333","DevoidSimo",[292,43,42,244,88,38],"23627853",[294,43,38,244,11,33],"23643664",[194,47,33,242,195,38],[297,18,33,242,298,38],"23628038","dnadler",[300,18,38,244,11,33],"23628092",[176,302,42,239,177,38],7,[71,302,38,244,11,33],[305,302,47,306,177,38],"23619255","project\u002Fpositive\u002Fperformance",[103,308,33,242,104,38],8,[310,308,38,244,11,33],"23620905",[312,308,42,244,225,38],"23620909",[129,40,33,314,130,38],"project\u002Fcritical\u002Fidea",[316,40,42,224,225,38],"23642864",[107,318,33,242,108,38],10,[320,318,38,244,11,33],"23619465",[151,322,42,224,152,38],11,[324,322,42,224,225,38],"23620286",[326,322,42,236,327,38],"23620326","helltone",[329,322,47,330,225,38],"23620358","maker\u002Fpositive\u002Fnone",[111,332,33,242,112,38],12,[334,335,33,242,336,38],"23620787",13,"timbowhite",[338,335,38,244,11,33],"23620881",[91,34,47,330,92,38],[341,34,38,236,11,33],"23622677",[343,344,42,224,345,38],"23621787",15,"heybrendan",[347,344,42,244,225,38],"23622345",[349,344,42,244,280,38],"23623262",[160,351,42,224,161,38],16,[353,351,42,224,354,38],"23619561","j1897",[356,357,33,242,358,38],"23623374",17,"jinmingjian",[360,357,42,361,240,38],"23626109","maker\u002Fneutral\u002Fexecution",[172,363,42,244,173,38],18,[365,363,38,216,11,33],"23621490",[367,363,42,244,173,38],"23621524",[369,363,42,244,225,38],"23621606",[371,204,47,372,373,38],"23624782","project\u002Fpositive\u002Fdesign","yingw787",[375,204,42,376,240,38],"23625927","maker\u002Fneutral\u002Fdesign",[378,204,47,372,373,38],"23630381",[380,204,42,376,240,38],"23641672",[382,383,42,384,385,38],"23624940",20,"project\u002Fmixed\u002Fdesign","greatNespresso",[387,383,42,376,388,38],"23625605","joan4",[390,391,42,252,392,38],"23624253",21,"RedShift1",[394,391,42,376,388,38],"23625671",[118,396,33,397,119,38],22,"project\u002Fcritical\u002Fdesign",[399,396,38,234,400,38],"23620713","dewey",[402,396,38,252,11,33],"23620728",[404,396,33,397,405,38],"23620858","shreddit",[407,396,38,376,11,33],"23620950",[409,396,38,234,410,38],"23620733","santafen",[412,396,33,397,413,38],"23620754","MarcellusDrum",[415,396,42,376,240,38],"23620927",[417,396,42,252,418,38],"23621126","thoraway1010",[420,396,38,421,240,38],"23621362","other\u002Fneutral\u002Fdesign",[164,423,42,239,165,38],23,[122,425,33,397,123,38],24,[427,425,42,376,225,38],"23619220",[429,425,33,242,430,38],"23620382","rkagerer",[432,425,38,216,11,33],"23620414",[434,425,47,435,240,38],"23619540","maker\u002Fpositive\u002Fdesign",[437,425,42,376,438,38],"23619893","cdubzzz",[440,425,38,376,11,33],"23619951",[442,425,42,376,438,38],"23620136",[444,425,38,421,445,38],"23619964","lowdose",[],[448,453,458,462,467,471],{"id":449,"name":450,"points":451,"category":452},"23591953","PJDL",337,"hardware",{"id":454,"name":455,"points":456,"category":457},"23610527","IHP",280,"languages",{"id":459,"name":460,"points":461,"category":457},"23602008","Web3Torrent",206,{"id":463,"name":464,"points":465,"category":466},"23595430","Browservice",193,"dev_tools",{"id":468,"name":469,"points":470,"category":457},"23612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