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Aggregator Leaf Tailer: An Alternative to Lambda Architecture for Real-Time Analytics

Rockset

Aggregator Leaf Tailer (ALT) is the data architecture favored by web-scale companies, like Facebook, LinkedIn, and Google, for its efficiency and scalability. In this blog post, I will describe the Aggregator Leaf Tailer architecture and its advantages for low-latency data processing and analytics.

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Exploring Processing Patterns For Streaming Data Integration In Your Data Lake

Data Engineering Podcast

What are the prevailing architectural and technological patterns that are being used to manage these systems? The Lambda architecture has largely been abandoned, so what is the answer for today’s data lakes? What are the most interesting, innovative, or unexpected ways that you have seen streaming architectures used?

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Simplifying Continuous Data Processing Using Stream Native Storage In Pravega with Tom Kaitchuck - Episode 63

Data Engineering Podcast

For someone who wants to build an application on top of Pravega, what interfaces does it provide and what architectural patterns does it lend itself toward? For someone who wants to build an application on top of Pravega, what interfaces does it provide and what architectural patterns does it lend itself toward?

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Rockset Architecture Whiteboard Session With CTO Dhruba Borthakur

Rockset

In this 30 minute video overview, CTO and Rockset Co-founder Dhruba Borthakur discusses Rockset's ALT architecture , how data is ingested, stored and queried in Rockset, and why Rockset is simple to use, incredibly fast, and capable of the highly efficient execution of complex distributed queries across diverse data sets.

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An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications

Data Engineering Podcast

Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

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Writing The Book That Offers A Single Reference For The Fundamentals Of Data Engineering

Data Engineering Podcast

Links Fundamentals of Data Engineering (affiliate link) Ternary Data Designing Data Intensive Applications James Webb Space Telescope Google Colossus Storage System DMBoK == Data Management Body of Knowledge DAMA Bill Inmon Apache Druid RTFM == Read The Fine Manual DuckDB Podcast Episode VisiCalc Ternary Data Newsletter Meroxa Podcast Episode Ruby (..)

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Unified Streaming And Batch Pipelines At LinkedIn: Reducing Processing time by 94% with Apache Beam

LinkedIn Engineering

In the past, we often used lambda architecture for processing jobs, meaning that our developers used two different systems for batch and stream processing. Architecture With our new architecture (as shown in Figure 3), developers only need to develop and maintain a single codebase written in Beam.

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