Software News

10 Hot Big Data Companies To Watch In 2023

Rick Whiting

Businesses are looking to big data tech developers to help them leverage exploding volumes of data for competitive advantage. Here’s a look at 10 hot big data companies – both startups and established companies – that the channel should keep an eye on this year.


Top Executive: Co-Founder and CEO Ali Ghodsi

Databricks is one of the leading cloud data service providers, competing with Snowflake, Cloudera and other cloud data platform companies with services around data analytics, data engineering, data governance, data sharing, machine learning and more.

The company is also the leading proponent of data lakehouse systems as an alternative to traditional data warehouses.

Databricks makes this “companies to watch” list because many observers expect that the company could move on its long-awaited – and highly anticipated – initial public offering (IPO) in 2023. Some expected that to happen in 2021 or 2022, but last year proved to be a debacle for technology stocks and IPOs were few and far between.

The San Francisco-based company has raised $3.5 billion in funding, including a $1.6 billion Series H funding round in September 2021 that boosted the company’s valuation to $38 billion.

In 2022 Databricks continued to expand its product portfolio, including launching data lakehouse packages for specific vertical markets including financial services, healthcare and life sciences, and retail and consumer goods. The company also launched its Brickbuilder Solutions initiative to help systems integrators, ISVs and other partners develop analytic and AI solutions on the Databricks Lakehouse Platform.


Rick Whiting

Rick Whiting has been with CRN since 2006 and is currently a feature/special projects editor. Whiting manages a number of CRN’s signature annual editorial projects including Channel Chiefs, Partner Program Guide, Big Data 100, Emerging Vendors, Tech Innovators and Products of the Year. He also covers the Big Data beat for CRN. He can be reached at

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