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InfluxData CEO, Evan Kaplan, talks about time series data workloads, how InfluxDB is purpose-built to support those workloads, and why that is so darn important.

Turn insights into action–in real-time–using your time series data. Now, more than ever, businesses generate massive amounts of time-stamped data. To get value from that data, you need to be able to ingest and query it in real-time. InfluxDB 3.0, built on innovative open source technology (Apache ecosystem), is the solution startups and enterprises use to achieve real-time insights.

InfluxData CEO, Evan Kaplan, sits down to talk about AI, how AI has become table stakes for modern software, and the role of time series data as a foundational component for building and training AI models.

InfluxData founder and CTO, Paul Dix, talks with CMO Brian Mullens about using InfluxDB 3.0 to bring real-time analytics to data lake and data warehouse architectures.

InfluxData Founder and CTO, Paul Dix, sits down to chat about real-time analytics, the role that time series data plays, and how a time series database complements data lakes and data warehouses for large workloads.

Paul Dix, founder and CTO of InfluxData, discusses how we built support for InfluxQL into the new InfluxDB 3.0, what the advantages of InfluxQL are, and how the broader open source ecosystem makes InfluxQL better.

InfluxData founder and CTO, Paul Dix, and VP of Product Marketing, Balaji Palani, talk about the product options available in InfluxDB 3.0 and what the ideal user for each one looks like, based on their data workloads.

High cardinality data presented a challenge to previous versions of InfluxDB, but InfluxDB 3.0 solved that problem. Influxers Jay Clifford and Zoe Steinkamp explain what cardinality is, why high cardinality impacts performance, and how InfluxDB 3.0 eliminates cardinality limits to open up new time series use cases.