How to Power Enterprises with Intelligent Applications with Jordan Tigani


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Jordan Tigani is Chief Product Officer at SingleStore. Tigani was formerly the director of product management for Google BigQuery. Prior to joining Google, a decade ago, Tigani had various engineering roles at early stage startups, and spent several years in the Windows kernel and Microsoft Research teams.

During his time at Google, he authored two books on Google BigQuery, and correctly predicted 14 out of 15 matches in the 2014 World Cup as part of an effort to demonstrate the power of integrating enterprise data warehouse and machine learning technologies. Tigani has an AB in Electrical Engineering from Harvard University, and an MS in Computer Science from University of Washington.

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Here’s the timestamps for the episode: 

(00:00) – Introduction

(01:38) –  I’m a product person now, but I’m really a software engineer at heart. I spent 20 years as an engineer and part of it as an engineering manager from Windows kernel to Microsoft research, worked at a couple of startups. It felt like MemSQL/SingleStore. They’ve got a burgeoning cloud product, they’re going in the right direction and they’re solving a problem that we were having a hard time-solving at Google and that problem was; how do you get analytics with very low latency? How do you get high update velocity for your analytic data store?

(06:10) –  One of the first things you want to do with analytics is you want to be able to display your data. Human beings are not very good at looking at columns of data and developing any patterns or recognizing any patterns. Every 10 milliseconds that it took for your query results to come back was additional time; you lose some percentage of users by making it just a tiny bit slower. And so, when you’re trying to get information from your data, when you’re trying to visualize your data, performance matters, speed matters. 

(09:36) –   By drilling down in your data, you can actually understand what’s going on in your business. At SingleStore performance matters and we can do analytics. A lot of our analytics queries that might take minutes elsewhere, we can do it in tens of milliseconds.

(11:37) – It sounds like that dashboard isn’t not such a big deal, but all the top execs use it. It does something like 800 queries per second, and an average latency of sub hundred milliseconds. And that scale lets them get the value and lets them become data-driven and make their decisions based on data and based on what’s happening right now.    

(13:21) –  One of the major telecom providers, we serve as the backend for all their analytics, for their 5G rollout. And we supported the rollout of their 5G systems. There are billions of records in this database. You need to be able to see what happens over time. You need to see the historical, but then you also need to be able to see it in real time. Financial services is one of the first areas where people get the value of real-time information. 

(17:52) – True Digital use cases is really interesting. They were able to basically use streaming information about, they used the cell phone location information, they were using that to generate heat maps and they can see where there were large COVID-19 infection rates.

(18:48) – If you’re building an application, it’s incredibly common to need some analytics, something that is going to let you say, like, ‘What’s going on in the world, what’s going on outside of the individual user or the individual data points you’re looking at?’ And just to give some examples of that, if you think about any leaderboard you’re going to show. if you’re building, if your application requires analytics; what are the things that you need? So you need the data to be up to date. And so the ingestion speed and the ingestion capacity is really important. 

(20:49) – The other thing that’s important is query performance. Your analytics queries have to be really fast because the responsiveness of your application is limited by the performance of these queries. If you’re building an application, you want that application to scale, to as many users as possible. You want to go viral. You want to have lots of people being able to hammer your system.

(24:52) –  One of the things about SingleStore and it’s the insight behind the name; it takes a lot of the different things that you would want to use your database for a lot of the different use cases. Whether it’s transactions, whether it’s analytics, whether it’s geospatial, whether it’s time series and it puts them all in one package and we can do a really good job of all these use cases. You have less things to manage. So lower cost of ownership, lower cost of having to train people in various tools.

(28:21) – I like the idea of using AI to augment and go beyond what you can do currently. There’s really intelligence, which is a step beyond analytics, which is driving real insight from the data and automatic insight from the data.

(30:22) – Middleware tools that allow you to get to the point where you’re making data-driven decisions by ensuring and asserting that your data is high quality. 

(34:33) –  SingleStore is going to be that database. It’s going to fuel the infrastructure and hopefully it’s going to make a lot of people look good for choosing it.