Postgres-powered AI: Running an End-to-End AI Platform with Postgres on Azure

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​ Video of a conference talk about Postgres-powered AI on Azure presented by Jaehyn Sim at POSETTE: An Event for Postgres 2024. Ikigai Labs’ AI platform, driven by Postgres, showcases its ability to handle diverse data types and benefit from a robust community ecosystem.

The platform’s success comes from Postgres’ ability to manage RDBMS advantages, such as ACID Compliance, alongside unstructured JSON data, ensuring compatibility with various data sources and programming languages. This versatility not only simplifies platform implementation but also enhances data interoperability of AI workloads.

The second pillar of Postgres’ strength is its extensive community support, enabling Ikigai to integrate numerous open-source tools. By leveraging Postgres as a metadata store, the platform ensures compatibility with various data ingestion, processing, and analysis tools. This integration, coupled with Postgres’ portability across cloud providers, enables Ikigai’s AI platform to be easily deployable in any cloud environment, as demonstrated by its successful recent migration to Azure.

Ikigai recently launched the Azure version of its platform, previously exclusive to AWS, with under 3 months of migration timeframe. This achievement underscores the benefits of Postgres as the sole database choice, enabling Ikigai to expedite its migration process and capitalize on the platform’s agility and scalability.

Jaehyun is the head of Engineering at Ikigai Labs, building a highly scalable and interactive AI platform for enterprise AI use cases. He is CNCF-certified CKA and CKAD and enjoys working with data warehouse/lakehouse, scalable distributed systems, and Kubernetes-related applications. He is currently working on making data operations more transparent by making data pipelines both massively scalable and easily visualizable. He has undergraduate degrees in Computer Science and Statistics from UC Berkeley and is currently studying system design and engineering management at MIT.

Chapters:
00:00 – Intro
04:03 – Data Ingestion with Postgres
06:24 – Data Processing with Postgres
07:32 – AI/ML Workloads with Postgres
09:22 – Data Visualization with Postgres
11:29 – An “Enterprise” AI Challenge
19:53 – Azure Compatibility Journey
23:07 – Summary

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Presenters:
Jaehyun Sim, Head of Engineering at Ikigai Labs

Connect:
Jaehyun Sim: https://www.linkedin.com/in/simjay/   Read More Microsoft Developer 

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