InfoQ Homepage Data Content on InfoQ
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Autonomous Data Products for the Autonomous Era: Rethinking Data Architecture for GenAI
Jörg Schad discusses how to bridge the gap between prototypes and production by standardizing data access for GenAI, using autonomous data products to prevent context rot and ensure safety.
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Accelerating Netflix Data: a Cross-Team Journey from Offline to Online
Raj Ummadisetty and Ken Kurzweil explain how Netflix transitioned its key-value abstraction from stateless to stateful, reducing data deployment time by 90% and infrastructure costs by 70%.
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Beyond Speed Limits: Exploring the Performance Power of Valkey
Viktor Vedmich explains how to achieve sub-millisecond application latency using Valkey, an open-source, high-performance in-memory fork of Redis supported by AWS.
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Architecting a Centralized Platform for Data Deletion at Netflix
Netflix Engineers Vidhya Arvind and Shawn Liu discuss the pillars of safe, large-scale data deletion. They explain strategies to eliminate data ghosts and manage tombstone resource contention.
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Are You Missing a Data Frame? The Power of Data Frames in Java
Vladimir Zakharov discusses the power of DataFrames in Java. He compares implementations like DataFrame-EC and Tablesaw against Python’s pandas, focusing on performance and memory efficiency.
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Powering Enterprise AI Applications with Data and Open Source Software
Francisco Javier Arceo explored Feast, the open-source feature store designed to address common data challenges in the AI/ML lifecycle, such as feature redundancy, and low-latency serving at scale.
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Reliable Data Flows and Scalable Platforms: Tackling Key Data Challenges
Matthias Niehoff discusses bridging the gap between application and data engineering. Learn to apply software engineering best practices, embrace boring technologies, and simplify architecture.
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Achieving Precision in AI: Retrieving the Right Data Using AI Agents
Adi Polak discusses achieving precision in GenAI by moving beyond RAG to Agentic RAG. She details agent patterns, feedback loops, and using data streaming architectures to scale real-time AI.
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The Data Backbone of LLM Systems
Paul Iusztin discusses the evolution of AI engineering, highlighting the shift from model training to foundational models. He shares insights on scalable LLM systems and optimizing RAG.
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Efficient Incremental Processing with Netflix Maestro and Apache Iceberg
Jun He discusses how to use an IPS to build more reliable, efficient, and scalable data pipelines, unlocking new data processing patterns.
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1BRC–Nerd Sniping the Java Community
Gunnar Morling discusses some of the tricks employed by the fastest solutions for processing a 13 GB input file within less than two seconds through parallelization and efficient memory access.
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Architecting for Data Products
Danilo Sato discusses what constitutes a data product and different types of data products, how data products support data architecture at different levels, skills and team topologies needed.
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