Guest: Arjun Narayan (LinkedIn)
Company: Materialize (Twitter)
Show: TFiR: T3M
Small and agile development teams are diving headfirst into the most robust cloud-enabled technology options to build with fast-changing data. In this episode of TFiR: T3M, Materialize Co-Founder and CEO Arjun Narayan gives us an insight into the evolution of data, the tooling around real-time datasets, how Materialize can help developers reap the benefits of real-time data, and more.
Highlights of this video interview:
- Materialize offers a data warehouse-like experience for building real-time applications, analytics and experiences with just SQL.
- It looks and feels exactly like a cloud data warehouse—You write SQL on top of your datasets and you get answers to complex analytics queries but just in milliseconds or tens of milliseconds. With Materialize, your answers are always up-to-date.
The Evolution of Data: Talking about the data stacks of the 90s, Narayan explains how the industry used to have data that was generated mostly by transactional databases. That was then an ETL out to a data warehouse, on premises on which would run a bunch of retrospective analysis.
The big data revolution, as we know it, began around two decades ago. What changed was, with the internet scale, datasets got larger and larger primarily as companies were collecting more data about each and every transaction.
In the early 2000s, the industry saw the first wave of pioneering frameworks such as Hadoop for reliably handling big data. Later, what changed with the cloud was the emergence of cloud-native data warehouses, which gave you all the benefits without having to roll your own infrastructure.
- Narayan believes where we are in real time parallels in many ways where we were with the Hadoop to the modern data stack.
- It’s very beneficial for organizations to be operating on real-time data. But similar to how the modern data stack enabled every organization to be data driven, a fully SQL experience where people can work with real-time data using just SQL will also enable every organization to be able to work with real-time data, and not just those that can build and scale and operate large distributed systems clusters in the cloud.
This summary was written by Monika Chauhan.