InfoQ Homepage Relational Databases Content on InfoQ
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Postgres for Production Agents: Your Relational Foundation for Enterprise AI
Gwen Shapira discusses how to power enterprise AI features using Postgres, explaining advanced relational SQL context retrieval, pgvector semantic tuning, and transitioning to agentic workflows.
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PRQL: a Simple, Powerful, Pipelined SQL Replacement
Aljaž Mur Eržen discusses PRQL, a language that can be compiled to most SQL dialects, which makes it portable and reusable, important factors of OLAP.
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PostgresML: Leveraging Postgres as a Vector Database for AI
Montana Low provides an understanding of how Postgres can be used as a vector database for AI and how it can be integrated into your existing application stack.
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Reactive Relational Database Connectivity with Spring
Mark Paluch explains R2DBC, how the API works, and the benefits for application developers who aim for functional reactive access with Spring Data R2DBC.
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Massively Scaling MySQL Using Vitess
Sugu Sougoumarane gives an overview of the salient features of Vitess, and at the end, covers some advanced features with a demo.
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RDBMS and Apache Geode Data Movement: Low Latency ETL Pipeline by Using Cloud-Native Event Driven Microservices
Paul Warren, Heather Riddle discuss how to create cloud-native event driven microservices for RDBMS and Apache Geode by using Cloud Foundry, Spring Cloud Stream, and RabbitMQ/Kafka.
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The Future of Distributed Databases Is Relational
Sumedh Pathak talks about his team’s journey to create a more modern relational database, distributed systems, scaling Postgres, distributed query planner and the distributed deadlock detection.
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Streaming SQL to Unify Batch & Stream Processing w/ Apache Flink @Uber
Shuyi Chen and Fabian Hueske explore SQL’s role in the world of streaming data and its implementation in Apache Flink and covering streaming semantics, event time, and incremental results.
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Gimel: PayPal’s Analytics Data Platform
Deepak Chandramouli introduces and demos Gimel, a unified analytics data platform which provides access to any storage through a single unified data API and SQL.
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Streaming SQL Foundations: Why I ❤ Streams+Tables
Tyler Akidau explores the relationship between the Beam Model and stream & table theory and explains what is required to provide robust stream processing support in SQL.
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Streaming SQL Foundations: Why I ❤Streams+Tables
Tyler Akidau explores the relationship between the Beam Model and stream & table theory, stream processing in SQL with Apache Beam, Calcite, Flink, Kafka KSQL and Apache Spark’s Structured streaming.
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Panel: SQL over Streams, Ask the Experts
The panelists discuss the new generation of Stream Processing engines.
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