InfoQ Homepage Database Content on InfoQ
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Lessons Learned from Building LinkedIn’s AI Data Platform
Felix GV provides an overview of LinkedIn’s AI ecosystem, then discusses the data platform underneath it: an open source database called Venice.
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LIquid: a Large-Scale Relational Graph Database
Scott Meyer discusses LIquid, the graph database built to host LinkedIn, serving a ~15Tb graph at ~2M QPS.
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Streaming Databases: Embracing the Convergence of Stream Processing and Databases
Yingjun Wu discusses the evolution of streaming databases, and the features and design principles that set streaming databases apart from conventional database systems and stream processing engines.
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Relational Data at the Edge
Justin Kwan and Vignesh Ravichandran discuss Cloudflare’s edge database architecture, unique challenges and practices for data replication, failover and recovery, and custom performance techniques.
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Redesigning OLTP for a New Order of Magnitude
Joran Greef discusses TigerBeetle, a new database, and why OLTP has a growing impedance mismatch, why the OLTP workload is becoming more contentious, why row locks, why storage faults, write stalls.
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Enabling Remote Query Execution through DuckDB Extensions
Stephanie Wang focuses on DuckDB’s extension model, and on query execution and planning, which is a use case of this DuckDB extension model.
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In-Process Analytical Data Management with DuckDB
Hannes Mühleisen discusses DuckDB, an analytical data management system that is built for an in-process use case. DuckDB speaks SQL, is integrated as a library, and uses query processing techniques.
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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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Ephemeral Execution is the Future of Computing, but What about the Data?
Jerop Kipruto and Christie Warwick use Tekton to explore challenges of data gravity in ephemeral execution, discussing clean container injection mechanisms and a secure server interface.
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Amazon DynamoDB Distributed Transactions at Scale
Akshat Vig explains how transactions were added to Amazon DynamoDB using a timestamp-based ordering protocol to achieve low latency for both transactional and non-transactional operations.
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Needle in a 930M Member Haystack: People Search AI @LinkedIn
Mathew Teoh explores how LinkedIn's People Search system uses ML to surface the right person that you're looking for.
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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.