Ajay Kulkarni's guest appearances

Ajay Kulkarni

Data Engineering Podcast

Open Source Underdogs

The Swyx Mixtape

Behind Company Lines

Alex Ratner

Mike Freedman

Bill Gates

Marc Andreessen

David Allen

Tim Urban

Adam Argyle

Paul Simon

Peter Attia

Cal Newport

Andrew Huberman

Taylor Negron

Peter Thiel

Zach Coelius

Seth Godin

OwlTail

Ajay Kulkarni is the CEO and Co-Founder of Timescale, creators of the industry-leading relational database for time series, built on the standards of PostgreSQL and SQL. With a focus on time-series data, his extensive experience has helped shape Timescale into a company dedicated to serving developers globally, enabling them to build the next wave of computing.  Timescale is backed by Benchmark, NEA, Redpoint, Tiger Global, Icon Ventures, and Two Sigma Ventures.Connect with Behind Company Lines and HireOtter   Website   Facebook  Twitter LinkedIn:Behind Company LinesHireOtter  Instagram Buzzsprout 

<p><a href="https://www.linkedin.com/in/ajaykulkarni/" rel="nofollow" target="_blank">Ajay Kulkarni</a> is the CEO and Co-Founder of <a href="https://www.timescale.com/" rel="nofollow" target="_blank">Timescale</a>, creators of the industry-leading relational database for time series, built on the standards of PostgreSQL and SQL. </p><p>With a focus on time-series data, his extensive experience has helped shape Timescale into a company dedicated to serving developers globally, enabling them to build the next wave of computing.  </p><p>Timescale is backed by Benchmark, NEA, Redpoint, Tiger Global, Icon Ventures, and Two Sigma Ventures.</p><p><br/><b>Connect with Behind Company Lines and HireOtter</b></p> <ul> <li> <a href="https://www.hireotter.com/" rel="nofollow" target="_blank">Website</a> </li> <li> <a href="https://www.facebook.com/otteratyourservice/" rel="nofollow" target="_blank">Facebook</a> </li> <li><a href="https://twitter.com/hireotter" rel="nofollow" target="_blank">Twitter</a></li> <li>LinkedIn:<br/><a href="https://www.linkedin.com/showcase/behind-company-lines/" rel="nofollow" target="_blank">Behind Company Lines</a><br/><a href="https://www.linkedin.com/company/hireotter/" rel="nofollow" target="_blank">HireOtter</a> </li> <li><a href="https://www.instagram.com/hireotter_/" rel="nofollow" target="_blank">Instagram</a></li> <li><a href="https://behindcompanylines.buzzsprout.com" rel="nofollow" target="_blank">Buzzsprout</a></li> </ul>

Ajay Kulkarni, CEO of Timescale

Michael Freedman

Timescale

full recording: https://share.transistor.fm/s/ae30126aTimescale Series C: https://news.ycombinator.com/item?id=30430000Timescale vs Influx: https://news.ycombinator.com/item?id=17766566Timescale vs Clickhouse: https://news.ycombinator.com/item?id=29096541Timescale launch: https://news.ycombinator.com/item?id=14984464

<p>full recording: <a href="https://share.transistor.fm/s/ae30126a" rel="nofollow" target="_blank">https://share.transistor.fm/s/ae30126a</a></p><p>Timescale Series C: <a href="https://news.ycombinator.com/item?id=30430000" rel="nofollow" target="_blank">https://news.ycombinator.com/item?id=30430000</a></p><p>Timescale vs Influx: <a href="https://news.ycombinator.com/item?id=17766566" rel="nofollow" target="_blank">https://news.ycombinator.com/item?id=17766566</a></p><p>Timescale vs Clickhouse: <a href="https://news.ycombinator.com/item?id=29096541" rel="nofollow" target="_blank">https://news.ycombinator.com/item?id=29096541</a></p><p>Timescale launch: <a href="https://news.ycombinator.com/item?id=14984464" rel="nofollow" target="_blank">https://news.ycombinator.com/item?id=14984464</a></p>

Time Series DB's: TimeScale [Ajay Kulkarni, Michael Freedman]

Summary As communications between machines become more commonplace the need to store the generated data in a time-oriented manner increases. The market for timeseries data stores has many contenders, but they are not all built to solve the same problems or to scale in the same manner. In this episode the founders of TimescaleDB, Ajay Kulkarni and Mike Freedman, discuss how Timescale was started, the problems that it solves, and how it works under the covers. They also explain how you can start using it in your infrastructure and their plans for the future. Preamble  Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at dataengineeringpodcast.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your data pipelines or trying out the tools you hear about on the show. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch. You can help support the show by checking out the Patreon page which is linked from the site. To help other people find the show you can leave a review on iTunes, or Google Play Music, and tell your friends and co-workers Your host is Tobias Macey and today I’m interviewing Ajay Kulkarni and Mike Freedman about Timescale DB, a scalable timeseries database built on top of PostGreSQL  Interview  Introduction How did you get involved in the area of data management? Can you start by explaining what Timescale is and how the project got started? The landscape of time series databases is extensive and oftentimes difficult to navigate. How do you view your position in that market and what makes Timescale stand out from the other options? In your blog post that explains the design decisions for how Timescale is implemented you call out the fact that the inserted data is largely append only which simplifies the index management. How does Timescale handle out of order timestamps, such as from infrequently connected sensors or mobile devices? How is Timescale implemented and how has the internal architecture evolved since you first started working on it?  What impact has the 10.0 release of PostGreSQL had on the design of the project? Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL?   For someone who wants to start using Timescale what is involved in deploying and maintaining it? What are the axes for scaling Timescale and what are the points where that scalability breaks down?  Are you aware of anyone who has deployed it on top of Citus for scaling horizontally across instances?   What has been the most challenging aspect of building and marketing Timescale? When is Timescale the wrong tool to use for time series data? One of the use cases that you call out on your website is for systems metrics and monitoring. How does Timescale fit into that ecosystem and can it be used along with tools such as Graphite or Prometheus? What are some of the most interesting uses of Timescale that you have seen? Which came first, Timescale the business or Timescale the database, and what is your strategy for ensuring that the open source project and the company around it both maintain their health? What features or improvements do you have planned for future releases of Timescale?  Contact Info  Ajay  LinkedIn @acoustik on Twitter Timescale Blog   Mike  Website LinkedIn @michaelfreedman on Twitter Timescale Blog   Timescale  Website @timescaledb on Twitter GitHub    Parting Question  From your perspective, what is the biggest gap in the tooling or technology for data management today?  Links  Timescale PostGreSQL Citus Timescale Design Blog Post MIT NYU Stanford SDN Princeton Machine Data Timeseries Data List of Timeseries Databases NoSQL Online Transaction Processing (OLTP) Object Relational Mapper (ORM) Grafana Tableau Kafka When Boring Is Awesome PostGreSQL RDS Google Cloud SQL Azure DB Docker Continuous Aggregates Streaming Replication PGPool II Kubernetes Docker Swarm Citus Data  Website Data Engineering Podcast Interview   Database Indexing B-Tree Index GIN Index GIST Index STE Energy Redis Graphite Prometheus pg_prometheus OpenMetrics Standard Proposal Timescale Parallel Copy Hadoop PostGIS KDB+ DevOps Internet of Things MongoDB Elastic DataBricks Apache Spark Confluent New Enterprise Associates MapD Benchmark Ventures Hortonworks 2σ Ventures CockroachDB Cloudflare EMC Timescale Blog: Why SQL is beating NoSQL, and what this means for the future of data  The intro and outro music is from The Hug by The Freak Fandango Orchestra  / CC BY-SASupport Data Engineering Podcast

<h2>Summary</h2> <p>As communications between machines become more commonplace the need to store the generated data in a time-oriented manner increases. The market for timeseries data stores has many contenders, but they are not all built to solve the same problems or to scale in the same manner. In this episode the founders of TimescaleDB, Ajay Kulkarni and Mike Freedman, discuss how Timescale was started, the problems that it solves, and how it works under the covers. They also explain how you can start using it in your infrastructure and their plans for the future.</p> <h2>Preamble</h2> <ul> <li>Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure</li> <li>When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at <a href="https://www.dataengineeringpodcast.com/linode?utm_source=rss&amp;utm_medium=rss" rel="nofollow" target="_blank">dataengineeringpodcast.com/linode</a> and get a $20 credit to try out their fast and reliable Linux virtual servers for running your data pipelines or trying out the tools you hear about on the show.</li> <li>Go to <a href="https://www.dataengineeringpodcast.com?utm_source=rss&amp;utm_medium=rss" rel="nofollow" target="_blank">dataengineeringpodcast.com</a> to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.</li> <li>You can help support the show by checking out the <a href="https://www.patreon.com/dataengineeringpodcast?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Patreon page</a> which is linked from the site.</li> <li>To help other people find the show you can leave a review on <a href="https://itunes.apple.com/us/podcast/data-engineering-podcast/id1193040557?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">iTunes</a>, or <a href="https://goo.gl/app/playmusic?ibi=com.google.PlayMusic&amp;isi=691797987&amp;ius=googleplaymusic&amp;link=https://play.google.com/music/m/Ivucmwlkrxbgfe5dhj562xgev4u?t%3DData_Engineering_Podcast%26pcampaignid%3DMKT-na-all-co-pr-mu-pod-16&amp;utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Google Play Music</a>, and tell your friends and co-workers</li> <li>Your host is Tobias Macey and today I’m interviewing Ajay Kulkarni and Mike Freedman about Timescale DB, a scalable timeseries database built on top of PostGreSQL</li> </ul> <h2>Interview</h2> <ul> <li>Introduction</li> <li>How did you get involved in the area of data management?</li> <li>Can you start by explaining what Timescale is and how the project got started?</li> <li>The landscape of time series databases is extensive and oftentimes difficult to navigate. How do you view your position in that market and what makes Timescale stand out from the other options?</li> <li>In your blog post that explains the design decisions for how Timescale is implemented you call out the fact that the inserted data is largely append only which simplifies the index management. How does Timescale handle out of order timestamps, such as from infrequently connected sensors or mobile devices?</li> <li>How is Timescale implemented and how has the internal architecture evolved since you first started working on it? <ul> <li>What impact has the 10.0 release of PostGreSQL had on the design of the project?</li> <li>Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL?</li> </ul> <p></p></li> <li>For someone who wants to start using Timescale what is involved in deploying and maintaining it?</li> <li>What are the axes for scaling Timescale and what are the points where that scalability breaks down?<p></p> <ul> <li>Are you aware of anyone who has deployed it on top of Citus for scaling horizontally across instances?</li> </ul> <p></p></li> <li>What has been the most challenging aspect of building and marketing Timescale?</li> <li>When is Timescale the wrong tool to use for time series data?</li> <li>One of the use cases that you call out on your website is for systems metrics and monitoring. How does Timescale fit into that ecosystem and can it be used along with tools such as Graphite or Prometheus?</li> <li>What are some of the most interesting uses of Timescale that you have seen?</li> <li>Which came first, Timescale the business or Timescale the database, and what is your strategy for ensuring that the open source project and the company around it both maintain their health?</li> <li>What features or improvements do you have planned for future releases of Timescale?</li> </ul><p></p> <h2>Contact Info</h2> <ul> <li>Ajay <ul> <li><a href="https://www.linkedin.com/in/ajaykulkarni/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">LinkedIn</a></li> <li><a href="https://twitter.com/acoustik?lang=en&amp;utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">@acoustik</a> on Twitter</li> <li><a href="https://blog.timescale.com/@acoustik?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Timescale Blog</a></li> </ul> <p></p></li> <li>Mike<p></p> <ul> <li><a href="http://www.cs.princeton.edu/~mfreed/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Website</a></li> <li><a href="https://www.linkedin.com/in/mfreed/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">LinkedIn</a></li> <li><a href="https://twitter.com/michaelfreedman?lang=en&amp;utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">@michaelfreedman</a> on Twitter</li> <li><a href="https://blog.timescale.com/@mike.freedman?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Timescale Blog</a></li> </ul> <p></p></li> <li>Timescale<p></p> <ul> <li><a href="http://www.timescale.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Website</a></li> <li><a href="https://twitter.com/timescaledb?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">@timescaledb</a> on Twitter</li> <li><a href="https://github.com/timescale/timescaledb?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">GitHub</a></li> </ul> <p></p></li> </ul><p></p> <h2>Parting Question</h2> <ul> <li>From your perspective, what is the biggest gap in the tooling or technology for data management today?</li> </ul> <h2>Links</h2> <ul> <li><a href="http://www.timescale.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Timescale</a></li> <li><a href="https://www.postgresql.org/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">PostGreSQL</a></li> <li><a href="https://www.citusdata.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Citus</a></li> <li><a href="https://blog.timescale.com/time-series-data-why-and-how-to-use-a-relational-database-instead-of-nosql-d0cd6975e87c?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Timescale Design Blog Post</a></li> <li><a href="http://web.mit.edu/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">MIT</a></li> <li><a href="https://www.nyu.edu/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">NYU</a></li> <li><a href="https://www.stanford.edu/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Stanford</a></li> <li><a href="https://en.wikipedia.org/wiki/Software-defined_networking?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">SDN</a></li> <li><a href="https://www.princeton.edu/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Princeton</a></li> <li><a href="https://en.wikipedia.org/wiki/Machine-generated_data?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Machine Data</a></li> <li><a href="https://en.wikipedia.org/wiki/Time_series?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Timeseries Data</a></li> <li><a href="https://misfra.me/2016/04/09/tsdb-list/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">List of Timeseries Databases</a></li> <li><a href="https://en.wikipedia.org/wiki/NoSQL?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">NoSQL</a></li> <li><a href="https://en.wikipedia.org/wiki/Online_transaction_processing?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Online Transaction Processing (OLTP)</a></li> <li><a href="https://en.wikipedia.org/wiki/Object-relational_mapping?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Object Relational Mapper (ORM)</a></li> <li><a href="https://grafana.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Grafana</a></li> <li><a href="https://www.tableau.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Tableau</a></li> <li><a href="https://kafka.apache.org/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Kafka</a></li> <li><a href="https://blog.timescale.com/when-boring-is-awesome-building-a-scalable-time-series-database-on-postgresql-2900ea453ee2?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">When Boring Is Awesome</a></li> <li><a href="https://www.postgresql.org/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">PostGreSQL</a></li> <li><a href="https://aws.amazon.com/rds/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">RDS</a></li> <li><a href="https://cloud.google.com/sql/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Google Cloud SQL</a></li> <li><a href="https://azure.microsoft.com/en-us/services/sql-database/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Azure DB</a></li> <li><a href="https://www.docker.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Docker</a></li> <li><a href="http://docs.pipelinedb.com/aggregates.html?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Continuous Aggregates</a></li> <li><a href="https://wiki.postgresql.org/wiki/Streaming_Replication?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Streaming Replication</a></li> <li><a href="http://pgpool.net/mediawiki/index.php/Main_Page?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">PGPool II</a></li> <li><a href="https://kubernetes.io/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Kubernetes</a></li> <li><a href="https://docs.docker.com/engine/swarm/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Docker Swarm</a></li> <li>Citus Data <ul> <li><a href="https://www.citusdata.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Website</a></li> <li><a href="https://www.dataengineeringpodcast.com/citus-data-with-ozgun-erdogan-and-craig-kerstiens-episode-13/?utm_source=rss&amp;utm_medium=rss" rel="nofollow" target="_blank">Data Engineering Podcast Interview</a></li> </ul> <p></p></li> <li><a href="https://en.wikipedia.org/wiki/Database_index?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Database Indexing</a></li> <li><a href="https://en.wikipedia.org/wiki/B-tree?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">B-Tree Index</a></li> <li><a href="https://www.postgresql.org/docs/current/static/gin-intro.html?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">GIN Index</a></li> <li><a href="https://www.postgresql.org/docs/current/static/gist-intro.html?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">GIST Index</a></li> <li><a href="http://www.sorgent-e.com/ste-energy?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">STE Energy</a></li> <li><a href="https://redis.io/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Redis</a></li> <li><a href="https://graphiteapp.org/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Graphite</a></li> <li><a href="https://prometheus.io/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Prometheus</a></li> <li><a href="https://github.com/timescale/pg_prometheus?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">pg_prometheus</a></li> <li><a href="https://github.com/RichiH/OpenMetrics?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">OpenMetrics Standard Proposal</a></li> <li><a href="https://github.com/timescale/timescaledb-parallel-copy?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Timescale Parallel Copy</a></li> <li><a href="http://hadoop.apache.org/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Hadoop</a></li> <li><a href="https://postgis.net/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">PostGIS</a></li> <li><a href="https://en.wikipedia.org/wiki/Kdb%2B?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">KDB+</a></li> <li><a href="https://en.wikipedia.org/wiki/DevOps?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">DevOps</a></li> <li><a href="https://en.wikipedia.org/wiki/Internet_of_things?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Internet of Things</a></li> <li><a href="https://www.mongodb.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">MongoDB</a></li> <li><a href="http://elastic.co/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Elastic</a></li> <li><a href="https://databricks.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">DataBricks</a></li> <li><a href="https://spark.apache.org/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Apache Spark</a></li> <li><a href="https://www.confluent.io/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Confluent</a></li> <li><a href="http://www.nea.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">New Enterprise Associates</a></li> <li><a href="https://www.mapd.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">MapD</a></li> <li><a href="https://en.wikipedia.org/wiki/Benchmark_(venture_capital_firm)?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Benchmark Ventures</a></li> <li><a href="https://hortonworks.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Hortonworks</a></li> <li><a href="https://www.twosigmaventures.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">2σ Ventures</a></li> <li><a href="https://www.cockroachlabs.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">CockroachDB</a></li> <li><a href="https://www.cloudflare.com/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Cloudflare</a></li> <li><a href="https://www.dellemc.com/en-us/index.htm?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">EMC</a></li> <li><a href="https://blog.timescale.com/why-sql-beating-nosql-what-this-means-for-future-of-data-time-series-database-348b777b847a?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">Timescale Blog: Why SQL is beating NoSQL, and what this means for the future of data</a></li> </ul><p></p> <p>The intro and outro music is from <a href="http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">The Hug</a> by <a href="http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">The Freak Fandango Orchestra</a>  / <a href="http://creativecommons.org/licenses/by-sa/3.0/?utm_source=rss&amp;utm_medium=rss" rel="noopener nofollow" target="_blank">CC BY-SA</a></p><p><a href="https://dataengineering.supercast.com/" rel="payment nofollow" target="_blank">Support Data Engineering Podcast</a></p>

TimescaleDB: Fast And Scalable Timeseries with Ajay Kulkarni and Mike Freedman - Episode 18