In a research paper recently published by the Institute of Electrical and Electronics engineers, researchers employed Deephaven to ingest and filter data before performing their tests and analytics. Read the full paper here.

Hubert Dulay interviewed our CEO Pete Goddard, CTO Ryan Caudy, and Lead Developer Devin Smith about the origins of Deephaven and its mission to provide a live data stack. Listen to the full interview on his podcast here.

Ryan Kavanahugh's comprehensive article in Data Intellect covers the basics of working with real-time data and how Deephaven makes it easy without sacrificing performance.

Open-source software empowers collaboration and innovation. Read more about Deephaven's particular strengths at handling real-time, dynamic data in the International Business Times.

Real-time data is essential to modern use cases, and for users to work productively, they need tables that change along with their data. Enter Deephaven's "streaming tables". Read more about Deephaven's unique, open-source software in Markets Insider from Business Insider.

How does one choose an image for a technical blog? You let the DALL-E AI bot do it for you! Paul Mah shares Deephaven's UX Designer Don McKenzie's findings in CDOTrends.

Also see this Techcrunch article quoting us on the same topic.

Our own Ryan Caudy talks about Deephaven's origin story and his personal successes on the FinTech CTO podcast with Vasyl Soloshchuk.

Watch on Youtube.

Datanami's Alex Woodie sits down with our CEO, Pete Goddard, to talk about Deephaven's real-time data capabilities and ease-of-use. Of note, Python users can now launch Core using pip. Covering its simple installation, streamlined table operations, and integration with Jupyter, the article highlights Deephaven's accessiblity to all users, despite their level of programming expertise.

Eric and Kostas from The Data Stack Show chat with Pete Goddard, the CEO of Deephaven, Arjun Narayan, co-founder and CEO of Materialize, Jeff Chao, a staff engineer at Stripe, and Ashley Jeffs, a software engineer at Benthos. Together they discuss batch versus streaming, transitioning from traditional data methods, and define “streaming ETL” as they push for simplicity across the board.

Watch on Youtube.

Conquering real-time data is the future of data science - but when it comes to AI, there are several roadblocks to overcome before you get it right. In his article published in Venture Beat, Chip Kent outlines strategies that put you on the easy path towards real-time AI.