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 60

Google Cloud Process Cloud Lambda Architecture 60

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 Datasets 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

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

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of acquiring and importing data for use, either immediately or in the future. This type of data ingestion leverages change data capture (CDC) to monitor transaction or redo logs on a constant basis, then move any changed data (e.g.,

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

dbt Developer Hub

JUNE 30, 2020

They literally cannot do their jobs without real-time data. If possible, the best thing to do is to query data as close to the source as possible. You don’t want to hit your production database unless you want to frighten and likely anger your DBA. What are lambda views? ​ Run dbt in micro-batches ​ Just don’t do it.

SQL 52

SQL Lambda Architecture Raw Data Architecture 52