Data Engineering Weekly

FEBRUARY 18, 2025

Fluss is a compelling new project in the realm of real-time data processing. In contrast, Fluss adopts a Lakehouse-native design with structured tables, explicit schemas, and support for all kinds of data types; it directly mirrors the Lakehouse paradigm. The second difference is the Storage Model.

Kafka 75

Kafka Lambda Architecture SQL Architecture 75

Towards Data Science

APRIL 30, 2024

Balancing correctness, latency, and cost in unbounded data processing Image created by the author. Intro Google Dataflow is a fully managed data processing service that provides serverless unified stream and batch data processing. Windowing The organizer Windowing divides the data into finite chunks.

Google Cloud 92

Google Cloud Process Cloud Lambda Architecture 92

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. Output is written to one or more databases.) A PTransform represents a data processing operation, or a step, in the pipeline.

Process 97

Process Lambda Architecture Kafka Architecture 97

LinkedIn Engineering

OCTOBER 19, 2023

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

Cloudera

NOVEMBER 2, 2020

An AdTech company in the US provides processing, payment, and analytics services for digital advertisers. Data processing and analytics drive their entire business. Data streamed in is queryable immediately, in an optimal manner. Data Model. Conventional enterprise data types. General Purpose RTDW.

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97

Rockset

MAY 12, 2022

Though some data sources like event streams were starting to arrive in real time, neither data nor queries were time sensitive. Databases could just buffer, ingest and query data on a regular schedule. Finally, you could always plan ahead for bursty traffic and overprovision your database clusters and pipelines.

Analytics Application 52

Analytics Application Lambda Architecture Hadoop Database 52

Ascend.io

JULY 28, 2023

Now, you might ask, “How is this different from data stack architecture, or data architecture?” ” Data Stack Architecture : Your data stack architecture defines the technology and tools used to handle data, like databases, data processing platforms, analytic tools, and programming languages.

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52