[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"sanity-CXLXdm2Qd-QYj913ER2qrm_wDvijD7emBtXGgT4u7VU":3,"sanity-mdEltNH_cANfKk5I2K_3cUqQfB4rJEIkhgfcvS6aFcA":250},{"data":4,"sourceMap":-1},{"latestPodcast":5,"latestReleases":14,"post":39,"recent":225},[6],{"_id":7,"publishedAt":8,"slug":9,"sponsored":12,"title":13},"7ebd76d2-cebc-4b88-82f9-3dfb2c8bc5ca","2026-07-08T04:40:00.000Z",{"_type":10,"current":11},"slug","what-s-left-for-infrastructure-as-code-after-ai-moves-in",true,"What's left for infrastructure-as-code after AI moves in?",[15,21,27,33],{"_id":16,"publishedAt":17,"slug":18,"title":20},"eb5b66eb-9410-4329-83bb-22bbff39402a","2026-04-28T13:00:00.000Z",{"_type":10,"current":19},"turn-scattered-knowledge-into-trusted-intelligence","Turning scattered knowledge into trusted intelligence: Stack Internal 2026.3",{"_id":22,"publishedAt":23,"slug":24,"title":26},"369c2401-b62e-4a37-8ff8-bf603023ecad","2026-03-02T15:03:00.988Z",{"_type":10,"current":25},"what-s-new-at-stack-overflow-march-2026","What’s new at Stack Overflow: March 2026",{"_id":28,"publishedAt":29,"slug":30,"title":32},"5e9053a4-07ea-447c-91ea-29e0b6228537","2026-02-02T15:00:00.000Z",{"_type":10,"current":31},"what-s-new-at-stack-overflow-february-2026","What’s new at Stack Overflow: February 2026",{"_id":34,"publishedAt":35,"slug":36,"title":38},"a1b538eb-a8a6-46d0-80a1-ac70ec9bb935","2026-01-05T10:00:00.000-05:00",{"_type":10,"current":37},"what-s-new-at-stack-overflow-january-2026","What’s new at Stack Overflow: January 2026",{"_createdAt":40,"_id":41,"_rev":42,"_type":43,"_updatedAt":44,"author":45,"body":61,"comments":12,"dateUrl":188,"excerpt":189,"image":190,"legacyBody":193,"product":76,"publishedAt":196,"slug":197,"sponsored":76,"tags":199,"title":224,"visible":12},"2023-05-24T12:50:58Z","wp-post-19636","NR627mkKF39ASec5MIcr3T","blogPost","2025-10-31T17:26:55Z",[46],{"_createdAt":47,"_id":48,"_rev":49,"_type":50,"_updatedAt":51,"avatar":52,"employee":57,"name":58,"slug":59},"2023-05-23T16:27:18Z","wp-author-226","dgl3SCUzppW3U2LvCoOzcS","blogAuthor","2023-06-20T15:05:06Z",{"_type":53,"asset":54},"image",{"_ref":55,"_type":56},"image-56688f6337dd0a96034dfc998cdecc7810597d81-1024x1024-png","reference","current","Ryan Donovan",{"current":60},"rdonovan",[62,73,78,98,117,125,133,141,149,168,179],{"_key":63,"_type":64,"children":65,"markDefs":71,"style":72},"afb20d667805","block",[66],{"_key":67,"_type":68,"marks":69,"text":70},"afb20d6678050","span",[],"These days, every company looking at analyzing their data for insights has a data pipeline setup. Many companies have a fast production database, often a NoSQL or key-value store, that goes through a data pipeline. The pipeline process performs some sort of extract-transform-load process on it, then routes it to a larger data store that the analytics tools can access. But what if you could skip some steps and speed up the process with a database purpose-built for analytics?",[],"normal",{"_key":74,"_type":75,"markDefs":76,"url":77},"7199fea2ddef","embed",null,"https:\u002F\u002Fart19.com\u002Fshows\u002F2355b740-4531-4071-a3ab-5907a95a36d3\u002Fepisodes\u002F327fd34c-e308-4aab-9fcc-bd132704535f",{"_key":79,"_type":64,"children":80,"markDefs":94,"style":72},"e33bd34ac0fb",[81,85,90],{"_key":82,"_type":68,"marks":83,"text":84},"e33bd34ac0fb0",[],"On this sponsored episode of the podcast, we chat with Rohit (Ro) Amarnath, the CTO at ",{"_key":86,"_type":68,"marks":87,"text":89},"e33bd34ac0fb1",[88],"1a4d6b5e5198","Vertica",{"_key":91,"_type":68,"marks":92,"text":93},"e33bd34ac0fb2",[],", to find out how your analytics engine can speed up your workflow. After a humble beginning with a ZX Spectrum 128, he’s now in charge of Vertica Accelerator, a SaaS version of the Vertica database.",[95],{"_key":88,"_type":96,"href":97,"reference":76},"link","https:\u002F\u002Fwww.vertica.com\u002F",{"_key":99,"_type":64,"children":100,"markDefs":114,"style":72},"02040e5d43d2",[101,105,110],{"_key":102,"_type":68,"marks":103,"text":104},"02040e5d43d20",[],"Vertica was founded by database researcher Dr. Michael Stonebreaker and Andrew Palmer. Dr. Stonebreaker helped develop several databases, including Postgres, Streambase, and VoltDB. Vertica was born out of research into purpose-built databases. Stonebreaker’s ",{"_key":106,"_type":68,"marks":107,"text":109},"02040e5d43d21",[108],"d27ec0feaa74","research",{"_key":111,"_type":68,"marks":112,"text":113},"02040e5d43d22",[]," found that columnar database storage was faster for data warehouses because there were fewer read\u002Fwrites per request.",[115],{"_key":108,"_type":96,"href":116,"reference":76},"http:\u002F\u002Fwww.csail.mit.edu\u002Fuser\u002F1547",{"_key":118,"_type":64,"children":119,"markDefs":124,"style":72},"1fbff83b1c06",[120],{"_key":121,"_type":68,"marks":122,"text":123},"1fbff83b1c060",[],"Here’s a quick example that shows how columnar databases work. Suppose that you want all the records from a specific US state or territory. There are 52 possible values here (depending on how you count territories). To find all instances of a single state in a row-based DB, the search must check every row for the value of the state column. However, searching by column is faster by an order of magnitude: it just runs down the column to find matching values, then retrieves row data for the matches.",[],{"_key":126,"_type":64,"children":127,"markDefs":132,"style":72},"4a45076cea92",[128],{"_key":129,"_type":68,"marks":130,"text":131},"4a45076cea920",[],"The Vertica database was designed specifically for analytics as opposed to transactional databases. Ro spent some time at a Wall Street firm building reports—P&L, performance, profitability, etc. Transactions were important to day-to-day operations, but the real value of data came from analyses that showed where to cut costs or increase investments in a particular business. Analytics help with overall strategy, which tends to be more far-reaching and effective.",[],{"_key":134,"_type":64,"children":135,"markDefs":140,"style":72},"4136ea9b5ff5",[136],{"_key":137,"_type":68,"marks":138,"text":139},"4136ea9b5ff50",[],"For most of its life, Vertica has been an on-premises database managing a data warehouse. But with the ease of cloud storage, Vertica Accelerator is looking to give you a data lake as a service. If you’re unfamiliar, data lakes take the data warehouse concept—central storage for all your data—and remove limits. You can have “rivers” of data flowing into your stores; if you go from a terabyte to a petabyte overnight, your cloud provider will handle it for you.",[],{"_key":142,"_type":64,"children":143,"markDefs":148,"style":72},"f037c1886536",[144],{"_key":145,"_type":68,"marks":146,"text":147},"f037c18865360",[],"Vertica has worked with plenty of industries that push massive amounts of data: healthcare, aviation, online games. They’ve built a lot of functionality into the database itself to speed up all manner of applications. One of their prospective customers had a machine learning model with thousands of lines of code that was reduced to about ten lines because so much was being done in the database itself.",[],{"_key":150,"_type":64,"children":151,"markDefs":165,"style":72},"94f24b5fc849",[152,156,161],{"_key":153,"_type":68,"marks":154,"text":155},"94f24b5fc8490",[],"In the future, Vertica plans to offer more powerful management of data warehouses and lakes, including handling the metadata that comes with them. To learn more about Vertica’s analytics databases, check out our conversation or visit their ",{"_key":157,"_type":68,"marks":158,"text":160},"94f24b5fc8491",[159],"a9c6e20ad9e2","website",{"_key":162,"_type":68,"marks":163,"text":164},"94f24b5fc8492",[],".",[166],{"_key":159,"_type":96,"href":167,"reference":76},"https:\u002F\u002Fwww.vertica.com\u002Fproduct\u002Fvertica-accelerator\u002F",{"_key":169,"_type":64,"children":170,"markDefs":176,"style":72},"a2ceb62fb873",[171],{"_key":172,"_type":68,"marks":173,"text":175},"a2ceb62fb8730",[174],"fd488ff8edca","TRANSCRIPT",[177],{"_key":174,"_type":96,"href":178,"reference":76},"https:\u002F\u002Fthe-stack-overflow-podcast.simplecast.com\u002Fepisodes\u002Fcolumn-by-your-name-the-analytics-database-that-skips-the-rows\u002Ftranscript\u002F",{"_key":180,"_type":64,"children":181,"markDefs":187,"style":72},"f1eaccaaa35f",[182],{"_key":183,"_type":68,"marks":184,"text":186},"f1eaccaaa35f0",[185],"em","The Stack Overflow blog is committed to publishing interesting articles by developers, for developers. From time to time that means working with companies that are also clients of Stack Overflow’s through our advertising, talent, or teams business. When we publish work from clients, we’ll identify it as Partner Content with tags and by including this disclaimer at the bottom.",[],"2022\u002F02\u002F16","What if you could get insights from data faster with a database purpose-built for analytics?",{"_type":53,"asset":191},{"_ref":192,"_type":56},"image-4e3e74ee47e0b795895f7e94f4dc679bd9e259dc-2400x1260-jpg",{"code":194,"language":195},"\u003C!-- wp:paragraph -->\n\u003Cp>These days, every company looking at analyzing their data for insights has a data pipeline setup. Many companies have a fast production database, often a NoSQL or key-value store, that goes through a data pipeline. The pipeline process performs some sort of extract-transform-load process on it, then routes it to a larger data store that the analytics tools can access. But what if you could skip some steps and speed up the process with a database purpose-built for analytics?\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:html -->\n\u003Ciframe height=\"200px\" width=\"100%\" frameborder=\"no\" scrolling=\"no\" seamless=\"\" src=\"https:\u002F\u002Fplayer.simplecast.com\u002F03711bb5-ca3e-4bb7-b5c8-cf3bc6724ee2?dark=false\">\u003C\u002Fiframe>\n\u003C!-- \u002Fwp:html -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>On this sponsored episode of the podcast, we chat with Rohit (Ro) Amarnath, the CTO at \u003Ca href=\"https:\u002F\u002Fwww.vertica.com\u002F\">Vertica\u003C\u002Fa>, to find out how your analytics engine can speed up your workflow. After a humble beginning with a ZX Spectrum 128, he’s now in charge of Vertica Accelerator, a SaaS version of the Vertica database. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Vertica was founded by database researcher Dr. Michael Stonebreaker and Andrew Palmer. Dr. Stonebreaker helped develop several databases, including Postgres, Streambase, and VoltDB. Vertica was born out of research into purpose-built databases. Stonebreaker’s \u003Ca href=\"http:\u002F\u002Fwww.csail.mit.edu\u002Fuser\u002F1547\">research\u003C\u002Fa> found that columnar database storage was faster for data warehouses because there were fewer read\u002Fwrites per request. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Here’s a quick example that shows how columnar databases work. Suppose that you want all the records from a specific US state or territory. There are 52 possible values here (depending on how you count territories). To find all instances of a single state in a row-based DB, the search must check every row for the value of the state column. However, searching by column is faster by an order of magnitude: it just runs down the column to find matching values, then retrieves row data for the matches. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The Vertica database was designed specifically for analytics as opposed to transactional databases. Ro spent some time at a Wall Street firm building reports—P&L, performance, profitability, etc. Transactions were important to day-to-day operations, but the real value of data came from analyses that showed where to cut costs or increase investments in a particular business. Analytics help with overall strategy, which tends to be more far-reaching and effective. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>For most of its life, Vertica has been an on-premises database managing a data warehouse. But with the ease of cloud storage, Vertica Accelerator is looking to give you a data lake as a service. If you’re unfamiliar, data lakes take the data warehouse concept—central storage for all your data—and remove limits. You can have “rivers” of data flowing into your stores; if you go from a terabyte to a petabyte overnight, your cloud provider will handle it for you. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Vertica has worked with plenty of industries that push massive amounts of data: healthcare, aviation, online games. They’ve built a lot of functionality into the database itself to speed up all manner of applications. One of their prospective customers had a machine learning model with thousands of lines of code that was reduced to about ten lines because so much was being done in the database itself. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>In the future, Vertica plans to offer more powerful management of data warehouses and lakes, including handling the metadata that comes with them. To learn more about Vertica’s analytics databases, check out our conversation or visit their \u003Ca href=\"https:\u002F\u002Fwww.vertica.com\u002Fproduct\u002Fvertica-accelerator\u002F\">website\u003C\u002Fa>.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fthe-stack-overflow-podcast.simplecast.com\u002Fepisodes\u002Fcolumn-by-your-name-the-analytics-database-that-skips-the-rows\u002Ftranscript\u002F\">TRANSCRIPT\u003C\u002Fa>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:separator -->\n\u003Chr class=\"wp-block-separator has-alpha-channel-opacity\"\u002F>\n\u003C!-- \u002Fwp:separator -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cem>The Stack Overflow blog is committed to publishing interesting articles by developers, for developers. From time to time that means working with companies that are also clients of Stack Overflow’s through our advertising, talent, or teams business. When we publish work from clients, we’ll identify it as Partner Content with tags and by including this disclaimer at the bottom.\u003C\u002Fem>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->","html","2022-02-16T15:13:04.000Z",{"current":198},"column-by-your-name-the-analytics-database-that-skips-the-rows",[200,208,210,214,219],{"_createdAt":201,"_id":202,"_rev":203,"_type":204,"_updatedAt":201,"slug":205,"title":207},"2023-05-23T16:43:21Z","wp-tagcat-partner-content","9HpbCsT2tq0xwozQfkc4ih","blogTag",{"current":206},"partner-content","Partner Content",{"_createdAt":201,"_id":202,"_rev":203,"_type":204,"_updatedAt":201,"slug":209,"title":207},{"current":206},{"_createdAt":201,"_id":211,"_rev":203,"_type":204,"_updatedAt":201,"slug":212,"title":213},"wp-tagcat-partnercontent",{"current":213},"partnercontent",{"_createdAt":201,"_id":215,"_rev":203,"_type":204,"_updatedAt":201,"slug":216,"title":218},"wp-tagcat-the-stack-overflow-podcast",{"current":217},"the-stack-overflow-podcast","the stack overflow podcast",{"_createdAt":201,"_id":220,"_rev":203,"_type":204,"_updatedAt":201,"slug":221,"title":223},"wp-tagcat-podcast",{"current":222},"podcast","The Stack Overflow Podcast","Column by your name: The analytics database that skips the rows",[226,232,238,244],{"_id":227,"publishedAt":228,"slug":229,"sponsored":76,"title":231},"76c9771b-34e6-4d98-8641-ecefc711f0ef","2026-07-06T15:23:34.559Z",{"_type":10,"current":230},"when-the-sensor-starts-thinking-snortml-agentic-ai-and-the-evolving-architecture-of-intrusion-detection","When the sensor starts thinking: SnortML, agentic AI, and the evolving architecture of intrusion detection",{"_id":233,"publishedAt":234,"slug":235,"sponsored":76,"title":237},"28e560af-f0aa-4d46-bd90-f435ad604aa7","2026-06-26T14:00:27.102Z",{"_type":10,"current":236},"paging-charity-how-can-engineering-leaders-avoid-becoming-bond-villains","Paging Charity! How can engineering leaders avoid becoming Bond villains?",{"_id":239,"publishedAt":240,"slug":241,"sponsored":76,"title":243},"4b22c2a3-3779-4966-93eb-5230391dbdce","2026-06-23T14:08:58.595Z",{"_type":10,"current":242},"your-ai-shipped-a-backend-that-boots-that-is-the-whole-problem","Your AI shipped a backend that boots. That is the whole problem.",{"_id":245,"publishedAt":246,"slug":247,"sponsored":76,"title":249},"5cf362e1-fe7b-45af-b69c-914731c6a052","2026-06-23T14:00:00.000Z",{"_type":10,"current":248},"the-2026-developer-survey-is-now-open-for-human-developers-only","The 2026 Developer Survey is now open (for human developers only)!",{"data":251,"sourceMap":-1},{"count":252,"lastTimestamp":76},0]