Berlin Open Source Data Infrastructure Meetup - April 2024

Are you interested in learning more about open-source data technologies? ✅
Do you want to network with local and international tech professionals in a fun, relaxed environment? ✅

Then join us on April 2, 2024, at the Aiven office in Berlin for an evening full of inspiring conversations and exciting talks!

• 17:30 - 18:00 Welcome: Networking & snacks, kickoff
• 18:00 - 18:30 Thoughtful Data Modeling
• Speakers: Celeste Horgan, Aiven, and Kevin Lewis, Directus
• How can we create data models that satisfy both user expectations and technical requirements? This talk explores balancing requirements of end-users, developers, and authors while answering questions like how to model product data without returning huge data objects, why do people put up with Midjourney's Discord generation, and when is near-realtime performance critical for meeting user expectations? This talk is for developers, UX designers, and data architects looking to enhance user experience through thoughtful data modeling.
• 18:30 - 19:00 Bringing Vectors to Postgres
• Speaker: Gülçin Yıldırım started working with Postgres at a startup company in 2012 and was amazed at how good Postgres really is! After being involved in organizing PostgreSQL conferences, giving talks, and being an active community member, she was elected to the PostgreSQL Europe Board in 2017. Gulcin is interested in PostgreSQL Automation and Cloud Technologies. She worked as Cloud Services Manager and led the Cloud Development in 2ndQuadrant (acquired by EDB in 2020). Gulcin is part of Postgres Women and cares about the diversity and representation of women in technical communities. She currently works at EDB as Staff Engineer.
• Postgres does not yet have native vector capabilities (as of Postgres 16) and pgvector is designed to fill this gap. You can store your vector data alongside the rest of your data in Postgres and do vector similarity search while still utilizing all the great features Postgres provides.
  The pgvector extension integrates seamlessly with Postgres – allowing users to leverage its capabilities within their existing database infrastructure. This simplifies the deployment and management of AI applications, as there's no need for separate data stores or complex data transfer processes.
  In this talk, we will learn how to generate and store vector embeddings in Postgres. We will discuss indexing (IVFFlat, HNSW) the embedding data and illustrate how to run a similarity query on our embeddings.
• 19:30 - 21:00 Food & Networking

* Please note that this is an alcohol-free event. Light bites will be provided.
* By attending this event, you agree to abide by our community code of conduct.