Data Engineering Podcast

NOVEMBER 20, 2021

What are the prevailing architectural and technological patterns that are being used to manage these systems? Batch and streaming systems have been used in various combinations since the early days of Hadoop. The Lambda architecture has largely been abandoned, so what is the answer for today’s data lakes?

Data Lake 100

Data Lake Data Integration Lambda Architecture Process 100

Rockset

FEBRUARY 6, 2019

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.

Lambda Architecture 40

Lambda Architecture Architecture MongoDB Kafka 40

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. Table of contents Before we move on Introduction from the paper.

Google Cloud 60

Google Cloud Process Cloud Lambda Architecture 60

Rockset

MAY 12, 2022

Database makers have experimented with different designs to scale for bursts of data traffic without sacrificing speed, features or cost. Lambda Architecture: Too Many Compromises A decade ago, a multitiered database architecture called Lambda began to emerge. One layer processes batches of historic data.

Analytics Application 52

Analytics Application Lambda Architecture Hadoop Database 52

Knowledge Hut

MAY 2, 2024

As per Apache, “ Apache Spark is a unified analytics engine for large-scale data processing ” Spark is a cluster computing framework, somewhat similar to MapReduce but has a lot more capabilities, features, speed and provides APIs for developers in many languages like Scala, Python, Java and R. billion (2019 - 2022).

Scala 52

Scala Hospitality Healthcare Machine Learning 52

ProjectPro

AUGUST 24, 2021

Learn how to process Wikipedia archives using Hadoop and identify the lived pages in a day. Utilize Amazon S3 for storing data, Hive for data preprocessing, and Zeppelin notebooks for displaying trends and analysis. Understand the importance of Qubole in powering up Hadoop and Notebooks.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52