Tales at Scale Imply Data

On this episode, we’re going all in on cybersecurity!  Helping us with what critical aspects of security you need to focus on when building analytics applications is Carrell Jackson, CISO at Imply. We’ll discuss the importance of protecting sensitive data by implementing role-based access control and encryption and hear about best practices for securing a Druid cluster. Listen to learn more about how Imply takes a security-first approach to their product development and stick around to hear where Certified Ethical Hacking fits into how Imply’s security stays ahead of threats.

On this episode, we explore Apache Druid 29.0, focusing on three specific themes: performance, ecosystem, and SQL compliance. Discover new features such as EARLIEST / LATEST support for numerical columns, system fields ingestion, and enhanced array support like UNNEST and JSON_QUERY_ARRAY. In addition, get the full scoop on community-contributed extensions like Spectator Histogram and DDsketch for efficient quantile calculations and long-tailed distribution support. Learn about what’s new with MSQ, what’s up with PIVOT / UNPIVOT, and so much more!

In this special episode of Tales at Scale - this is our final episode of our first season! - Peter Marshall, Director of Developer Relations at Imply joins the show to discuss the highlights of 2023 for Apache Druid. We dive into the significant feature releases and enhancements that have transformed Druid over the past year, including the SQL standardizaion, query from deep storage, experimental window functions, and the growing Druid community. Come for the retrospective, stay for the peek into the future of what’s to come for us and for Druid in 2024. See you all next year!

On this episode, we dive into Apache Druid 28. This latest Druid release includes improved ANSI SQL and Apache Calcite support, the addition of window functions as an experimental feature, async queries and query from deep storage going GA, array enhancements, multi-topic Apache Kafka ingestion, and so much more! Will Xu, program manager at Imply returns to give us the full scoop.

On this episode, we debunk the myth that Druid can't do joins. Druid doesn't function as a traditional relational database because it was purpose-built for lightning-fast queries on large datasets. However, this doesn't mean Druid is entirely devoid of join capabilities – it simply approaches them differently. Our myth-busting team features returning guests Sergio Ferragut and Hellmar Becker from Imply ready to clarify how Druid handles joins in its own unique way and tackle what Druid is for in the first place. 

On this episode, we explore how Atlassian leverages Apache Druid's capabilities to handle millions of daily events and empower users with intelligent data-driven features. We’re joined by Gautam Jethwani and Kasirajan Selladurai Selvakumari from the Confluence Big Data Platform Team who will talk through how they use Druid to power intelligent features, sub-second query latency, and complex ingestion tasks.