Interview: Tomer Shiran, Co-founder and CEO at Dremio

Print Friendly, PDF & Email

I recently caught up with Tomer Shiran, Co-founder and CEO at Dremio, to discuss his new company that just came out of stealth. Dremio is an open source software start-up based in Mountain View, and was built on the idea that companies need to change that dynamic between the consumers of data and IT. Dremio’s strategy is based on the premise that data consumers have too many tools, which creates unnecessary complexity and user headaches, particularly in mixed environments involving traditional and emerging platforms. Dremio simplifies the process of connecting, preparing and querying data in multiple different repositories in order to give data consumers a better experience when analyzing the data in their analysis tool of choice. Prior to Dremio, Tomer was the VP Product at MapR, where he was responsible for product strategy, roadmap, and new feature development. As a member of the executive team, he helped grow the company from 5 employees to over 300 employees and 1000 enterprise customers. Prior to MapR, he held numerous product management and engineering positions at Microsoft and IBM Research. Tomer holds an MS in Electrical and Computer Engineering from Carnegie Mellon University and a BS in Computer Science from Technion – Israel Institute of Technology. He is also the author of five US patents.

Daniel D. Gutierrez – Managing Editor, insideAI News

insideAI News: Dremio just came out of stealth. Can you tell us about the genesis of the company and the team you have in place?

Tomer Shiran: It’s a great time to be a developer – you can download MongoDB, Hbase, Elasticsearch, Hadoop – all very scalable, open source, free, great APIs – to build apps fast. However, for business analysts and data scientists, life isn’t so great. They can’t connect their BI tools like Tableau, Qlik, Power BI to these data warehousing systems like Teradata and Vertica. It’s too slow and too hard. So, they end up spending 90% of the time collecting data rather than analyzing it. Centralizing all your data from varied data warehouses to use Tableau, and the other BI connector tools is painful for IT and data engineering. For example, adding a column to their data warehouse adds 9 months and millions of dollars and the data is stale and summarized and often not what was requested anyway.

When Amazon introduced AWS, they introduced a self-service model for infrastructure, liberating developers, and transforming the market. We created Dremio to do for data what AWS did for infrastructure, freeing analysts and data scientists to use data from any source and at any scale, at unprecedented speed, while preserving governance and security. Our vision is that all of your data is just one SQL query away.

Dremio is a dream team of veterans in big data and open source from companies including MapR, MongoDB, and Hortonworks, Twitter, and Apple. Our co-founder Jacques Nadeau, is the PMC Chair of Apache Arrow.

insideAI News: How do you make “big data” seem small?

Tomer Shiran: Dremio makes data easy, approachable, and interactive, no matter how many terabytes, no matter where it’s stored. Dremio optimizes data so you analysts don’t have to – making it seem small.

Working with existing data sources and business intelligence tools, Dremio’s self-service data platform eliminates the need for traditional ETL and data warehousing. Dremio’s analyst cloud solution, combines consumer-grade ease-of-use with enterprise-grade security and governance, and includes ground-breaking execution and caching technologies that dramatically speed up queries.

We provide a future proof strategy for data, allowing customers to choose the best tools for their analysts, and the right database technology for their apps, without compromising on their ability to leverage data to drive the business. Because Dremio can be run in a dedicated cluster, in the cloud or on prem, or as a service provisioned and managed in a Hadoop cluster, customers can easily scale Dremio to meet their needs at any scale.

insideAI News: Tell us about how your solutions bring agility to enterprise analytics?

Tomer Shiran: Dremio transparently enables unprecedented time to insight. Unlike traditional approaches, which require building a data warehouse or rely on point to point single server designs, Dremio connects any analytical process to any data source and scales from one to 1000 plus servers, running on dedicated hardware or in a Hadoop cluster.

With Dremio business users can perform critical data tasks themselves, without being dependent on IT. Companies like Tableau brought self-service to BI. We bring self-service to all the other layers of the analytics stack, including ETL and data warehousing, which are entirely IT-driven today.

Customers can easily discover data from a comprehensive catalog, work together as teams to curate and share virtual datasets, and run analytical jobs through Dremio from any BI or data science tool.

insideAI News: Can you describe your target user, data analyst, data scientist, both?

Tomer Shiran: Because we make running queries on any data set using favorite BI tools so easy, we empower data analysts and data scientists to spend their time accelerating analytics and getting fast insights from their data. We are selling to F500 companies, or any large organization that has data in multiple systems. Because Dremio is open source, we expect companies of all sizes, industries, and geographies to use Dremio to make their analysts, data scientists, and data engineers more productive.

insideAI News: What are you plans for the rest of 2017 and into 2018?

Tomer Shiran: We launched with our community and enterprise editions so you should expect to see us build out both of these with new innovations, as well as more partnerships, and offerings optimized for cloud.


Sign up for the free insideAI News newsletter.

Speak Your Mind