Data Engineering Weekly

FEBRUARY 18, 2025

It addresses many of Kafka's challenges in analytical infrastructure. The combination of Kafka and Flink is not a perfect fit for real-time analytics; the integration of Kafka and Lakehouse is very shallow. How do you compare Fluss with Apache Kafka? Fluss and Kafka differ fundamentally in design principles.

Kafka 75

Kafka Lambda Architecture SQL Architecture 75

Data Engineering Podcast

JUNE 1, 2020

What used to be entirely managed by the database engine is now a composition of multiple systems that need to be properly configured to work in concert. What used to be entirely managed by the database engine is now a composition of multiple systems that need to be properly configured to work in concert.

Data Lake 100

Data Lake Database Building Lambda Architecture 100

Data Engineering Podcast

MAY 11, 2020

With real time alerts for problems in your databases, ETL pipelines, or data warehouse, and integrations with Slack, Pagerduty, and custom webhooks you can fix the errors before they become a problem. How have projects such as Kafka and Pulsar impacted the broader software and data landscape? When is Pulsar the wrong choice?

Cloud 100

Cloud Lambda Architecture Kafka Hadoop 100

Data Engineering Podcast

AUGUST 21, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Just connect it to your database/data warehouse/data lakehouse/whatever you’re using and let them do the rest.

Lambda Architecture 100

Lambda Architecture MongoDB MySQL Scala 100

LinkedIn Engineering

OCTOBER 19, 2023

In 2010, they introduced Apache Kafka , a pivotal Big Data ingestion backbone for LinkedIn’s real-time infrastructure. To transition from batch-oriented processing and respond to Kafka events within minutes or seconds, they built an in-house distributed event streaming framework, Apache Samza.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

LinkedIn Engineering

MARCH 23, 2023

In the past, we often used lambda architecture for processing jobs, meaning that our developers used two different systems for batch and stream processing. This pipeline reads ProfileData; joins the data with sideTable and then applies a user defined function called Standardizer(); finally, writes the standardized result to databases.

Process 97

Process Lambda Architecture Kafka Architecture 97

Cloudera

NOVEMBER 2, 2020

So they needed a data warehouse that could keep up with the scale of modern big data systems , but provide the semantics and query performance of a traditional relational database. Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. They chose to build their RTDW on Cloudera.

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97