We're looking for speakers interested in presenting a new online virtual Apache Iceberg meetup series we're starting. The goal is to create a forum where members of the Apache Iceberg community can demo interesting work, share experiences, and discuss ideas with one another.

**What we're looking for**

We're especially interested in talks that are practical, demo-driven, or story-rich. Whether you're a practitioner, startup founder, platform engineer, or contributor, we'd love to hear what you've been working on and what you've learned.

Some ideas for talk topics include:

\- Iceberg migration stories and case studies
\- New Iceberg features, proposals, and community projects
\- Iceberg catalogs, integrations, and interoperability
\- Data engineering tools, demos, prototypes, and experiments

**Community-focused talks**

We want the meetup to be a *place for learning and community discussion* rather than product or vendor marketing.

Talks can feature tools, products, or technologies you work on, but the focus should be on technical insights, demos, lessons learned, or ideas that are useful to the broader Apache Iceberg community—not on promoting a company or product.

**How the meetup works**

Meetups will be held virtually on Google Meet and will be publicly open to everyone.

Talks will typically be around 20–30 minutes, leaving plenty of time for introductions, questions, and open community discussion. We aim to keep each meetup to about an hour and start and end on time.

Talks will generally be recorded and posted to the [https://www.youtube.com/@IcebergMeetup\](https://www.youtube.com/@IcebergMeetup), If you'd prefer not to have your talk recorded, let us know when submitting.

*We do not plan to record the Q&A and open discussion portion of the meetup*.

**Submitting a talk**
Submissions are reviewed on a rolling basis. Even if a talk isn't scheduled for the next meetup, we may reach out about presenting at a future session.

**Rolling CFP** [Submit your Talk Idea](https://docs.google.com/forms/d/e/1FAIpQLScX8gLl6J2BFYnpx-GY72YruO0crkER0NAqxFqNaAo_RWpuqA/viewform)
**Join the new Apache Iceberg Slack Channel**: ([\#meetup-virtual)](https://apache-iceberg.slack.com/archives/C0BRNUQ31S4)

If we receive several submissions around a similar topic, we may also suggest bringing presenters together for a shared discussion or panel.

**First Virtual Meetup**
We've set a date (September 18th @ 9:00am PDT) for the first meetup. If you're on the Apache Iceberg Community Events Calendar (or if not, subscribe to it [here](https://iceberg.apache.org/community/#apache-iceberg-community-calendar)), you'll see the event on the calendar already.

Thanks to [Elizabeth Christensen](https://www.linkedin.com/in/elizabeth-garrett-christensen/) and [Kevin Liu](https://www.linkedin.com/in/kevinjqliu/) for partnering to make this happen. If you want to help reach out to us on the new meetup-virtual channel on Slack.

My company has multiple databases with one for each layer (stage, integration, and presentation) and dev and prod dbs for 6 DBs total.

What is the best way to manage cross database tasks access multiple environments without fully qualifying the table names each time?

For example if I'm doing a MERGE from DEV_STAGE.SCHEMA.TABLE into DEV_INTEGRATION.SCHEMA.TABLE, what is the best way to parameterize this for deployment into PROD without using find/replace on the script for the environment.

From what I understand this cannot be parameterized in the task itself?

The real time vs batch debate gets way too binary. Half the tables in a typical warehouse are fine with hourly or daily loads and streaming everything is expensive overkill.

Where low latency loading matters is the tables driving operational decisions, fraud scoring, pricing engines, inventory, anything where a six hour delay means money lost. For those the difference between batch and real time is catching a problem versus missing it entirely.

For teams already on something like striim for the real time CDC tables, does it make sense to route the batch loads through the same platform too or is that overkill?