From Raw Ticks to Candlesticks | Optimizing Crypto Data in TimescaleDB

In this step-by-step tutorial from @DatabaseStar we’ll go beyond setup and dive into optimizing crypto time-series data. You’ll learn how to use continuous aggregates, compression, and candlestick visualizations in Grafana to make your database faster and more efficient. Perfect for developers analyzing financial or blockchain data. 🛠 𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝘁 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 📌 Sign up for FREE ⇒ https://tsdb.co/td-yt 📌 Watch part 1 ⇒ https://www.youtube.com/watch?v=ERtcMDuPVnU 💻 𝗙𝗶𝗻𝗱 𝗨𝘀 𝗢𝗻𝗹𝗶𝗻𝗲! 🔍 Website ⇒ https://tsdb.co/homepage 🔍 Slack ⇒ https://slack.timescale.com 🔍 GitHub ⇒ https://github.com/timescale 🔍 Twitter ⇒ https://twitter.com/timescaledb 🔍 LinkedIn ⇒ https://www.linkedin.com/company/tigerdata 🔍 Tiger Data Blog ⇒ https://tsdb.co/blog 🔍 Tiger Data Documentation ⇒ https://tsdb.co/docs 📚 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀 ⏱ 0:00 ⇒ Introduction ⏱ 0:30 ⇒ Recap of Part 1 ⏱ 0:50 ⇒ Creating a Candlestick Visualization ⏱ 1:24 ⇒ Using TimescaleDB Hyperfunctions ⏱ 3:01 ⇒ Continuous Aggregate Usage ⏱ 4:25 ⇒ Building a Candlestick Chart in Grafana ⏱ 5:53 ⇒ Compressing old Data to Save Space ⏱ 7:30 ⇒ Wrap up and How to try for Free