Systems | Development | Analytics | API | Testing

How to Analyze Data from a REST API with Flink SQL

Join Lucia Cerchie in a coding walkthrough, bridging the gap between REST APIs and data streaming. Together we’ll transform the OpenSky Network's live API into a data stream using Kafka and Flink SQL. Not only do we change the REST API into a data stream in this walkthrough, but we clean up the data on the way! We use Flink SQL to make it more readable and clean, and in that way we keep more of the business logic away from the client code.

What is Streaming ETL?

Streaming ETL is a modern approach to extracting, transforming, and loading (ETL) that processes and moves data from source to destination in real-time. It relies on real-time data pipelines that process events as they occur. Events refer to various individual pieces of information within the data stream. Depending on the source and purpose of the data, an event could be a single user visit to a website, a new post on a social media platform, or a data point from a temperature sensor.

Databricks vs. Snowflake: A Comparative Analysis

With the data management landscape continuously evolving, it has given rise to powerful platforms like Databricks and Snowflake, each offering distinct capabilities for organizations to manage and analyze their data efficiently. Our 5 key takeaways in the Databricks vs. Snowflake debate are: In this article, we will dive into a comprehensive comparison of Databricks and Snowflake and examine the data companies’ features, performance, scalability, and more.

Marketing and Sales in Uncertain Times: Strategies & Spending Impact (2024)

Enjoy reading this blog post written by our experts or partners. If you want to see what Databox can do for you, click here. No matter what size your business is or what market you operate in, there’s one thing every business will confirm – marketing and sales during a downturn can be extremely challenging. But that doesn’t mean you should turn off the tap on marketing and sales until things get better.

Simplified End-to-End Development for Production-Ready Data Pipelines, Applications, and ML Models

In today’s world, innovation doesn’t happen in a vacuum; collaboration can help technological breakthroughs happen faster. The rise of AI, for example, will depend on the collaboration between data and development. We’re increasingly seeing software engineering workloads that are deeply intertwined with a strong data foundation.

Snowflake Massively Expands Types of Applications That Can Be Built, Deployed and Distributed on Snowflake

Apps are the way to democratize AI: to make it accessible to everyone and streamline customers’ experiences with faster time to insights. According to a recent IDC survey, AI applications is currently the largest category of AI software, accounting for roughly one-half of the market’s overall revenue in 2023.