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.
Deephaven's Productive-Boosting streaming tables in Business Insider
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.
Deephaven's AI-generated blog redesign featured in CDOTrends and Techcrunch
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.
From Bloomberg to Deephaven: Ryan Caudy on the FinTech CTO podcast
Our own Ryan Caudy talks about Deephaven's origin story and his personal successes on the FinTech CTO podcast with Vasyl Soloshchuk.
Datanami feature on Deephaven's real-time analytics
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.
Discussing the future of streaming data with Deephaven, Materialize, Stripe, and Benthos
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.
Featured in Venture Beat
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.
Data Science At Home podcast featuring Chip Kent
If you're a data scientist, and you're not using real-time data yet, you will be soon. In this episode of the Data Science at Home podcast, "Streaming data with ease," Chip Kent and Francesco Gadaleta talk about the imperative of working with real-time data and the challenges that go along with it. A real-time stream by definition is constantly growing - there is no end to your data. Chip and Francesco discuss useful tools and best practices for data scientists and engineers to help navigate this new territory.
Python Madness
In this article from Inside Big Data, our CEO, Pete Goddard, talks about Deephaven's Python Package MVP tournament, what the match-ups say about the Python community's preferences, and the popularity of Python in data science in general.
How to write documentation users want to read
Tammy Xu for Built In magazine interviewed several developers and technical writers, including our own dev-rel engineer Amanda Martin, to discuss the challenges of writing useful software documentation. In particular, Martin highlights the need to cater to users of different levels as well as continually maintaining working examples so users never feel frustrated.