Open table formats such as Apache Iceberg or Delta Lake have transformed
the data landscape. For the first time, we’re seeing a real open storage
ecosystem emerging across database vendors.
So far, open table formats have found little adoption powering low-latency,
high-concurrency analytics use-cases. Data stored in open formats often
gets transformed and ingested into closed systems for serving.
The reason for this is simple: most modern query engines don’t properly
support these workloads. In this talk we take a look under the hood of Firebolt
and dive into the work we’re doing to support low-latency and high
concurrency on Iceberg: caching of data and metadata, adaptive object
storage reads, subresult reuse, and multi-dimensional scaling.
After this session, you will know how you can build low-latency data
applications on top of Iceberg. You’ll also have a deep understanding of what
it takes for modern high-performance query engines to do well on these
workloads.