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The evolution of Facebook’s iOS app architecture

Engineering at Meta

Objects in Core Data are mutable, and that did not lend itself well to News Feed’s multithreaded architecture. It was clear that this architecture was not sustainable and it was time to rethink it. This information would be the building block of the app’s next generation of architecture. a(FBSomeFile.mm.o)

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Exploring Data Mesh: A Paradigm Shift in Data Architecture

KDnuggets

Let’s explore Data Mesh, a modern approach to data architecture that decentralizes data ownership and management.

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Addressing The Challenges Of Component Integration In Data Platform Architectures

Data Engineering Podcast

In this episode Tobias Macey shares his thoughts on the challenges that he is facing as he prepares to build the next set of architectural layers for his data platform to enable a larger audience to start accessing the data being managed by his team. With Materialize, you can! Want to see Starburst in action? Want to see Starburst in action?

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Apache Druid’s Architecture – How Druid Processes Data In Real Time At Scale

Seattle Data Guy

Now I wanted to do a deeper dive into Apache Druid’s architecture. Everything from its various nodes and processes that each have unique… Read more The post Apache Druid’s Architecture – How Druid Processes Data In Real Time At Scale appeared first on Seattle Data Guy.

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Modern Data Architecture for Embedded Analytics

Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind. 9 questions to ask yourself when planning your ideal architecture.

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They Handle 500B Events Daily. Here’s Their Data Engineering Architecture.

Monte Carlo

A data engineering architecture is the structural framework that determines how data flows through an organization – from collection and storage to processing and analysis. Before building your own data architecture from scratch though, why not steal – er, learn from – what industry leaders have already figured out?

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Modern Data Architecture: Data Mesh and Data Fabric 101

Precisely

Data mesh and data fabric are two modern data architectures that serve to enable better data flow, faster decision-making, and more agile operations. Both architectures share the goal of making data more actionable and accessible for users within an organization.

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Embedding BI: Architectural Considerations and Technical Requirements

Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures. Holding onto old BI technology while everything else moves forward is holding back organizations.

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Apache Airflow® Best Practices for ETL and ELT Pipelines

ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines.

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Best Practices for Deploying & Scaling Embedded Analytics

Read more about how to simplify the deployment and scalability of your embedded analytics, along with important considerations for your: Environment Architecture: An embedded analytics architecture is very similar to a typical web architecture. Deployment: Benefits and drawbacks of hosting on premises or in the cloud.