Silos and inconsistency top list of data challenges for global IT leaders
New research from Confluent sees IT leaders share their biggest data challenges.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
How Booking.com Used Data Streaming to Put Travel Decisions into Customer's Hands
Booking.com wanted to give people a “connected trip” experience, allowing customers to seamlessly book flights, accommodations, car rentals, and excursions in one visit. The company realized the value of data streaming early on in reaching this goal, but the operational effort had become overwhelming. Learn how Booking.com found the answer in Confluent’s data streaming platform. With its automated configuration that required no ongoing maintenance, the team was able to prioritize innovation with data and provide the comprehensive booking experience they had been searching for.
Your Guide to the Apache Flink Table API: An In-Depth Exploration
Apache Flink offers a variety of APIs that provide users with significant flexibility in processing data streams. Among these, the Table API stands out as one of the most popular options. Its user-friendly design allows developers to express complex data processing logic in a clear and declarative manner, making it particularly appealing for those who want to efficiently manipulate data without getting bogged down in intricate implementation details.
Expanding Confluent's Integration with Microsoft Azure: Create and Manage Confluent Resources Directly from the Azure Portal with Confluent's Fully Managed Connectors (Preview)
We are thrilled to announce yet another milestone in our integration capabilities with Microsoft Azure. Now, you can manage Confluent resources (Preview) directly from the Azure portal. This new capability not only simplifies the setup and management process but also empowers you to leverage the full potential of Confluent's data streaming platform on Azure.
Atomic Tessellator: Revolutionizing Computational Chemistry with Data Streaming
Computational chemistry relies on large volumes of complex data in order to provide insights into new applications, whether it’s for electric vehicles or new battery development. With the emergence of generative AI (GenAI), the rapid, scalable processing of this data has become possible and critical to investigate previously unexplored areas in catalysis and materials science.
How to source data from AWS DynamoDB to Confluent using the Open-Source Connector
This is a one-minute video showing an animated architectural diagram of an integration between Amazon DynamoDB and Confluent Cloud using an open-source Kafka connector. The integration allows you to avoid maintaining custom code, and gives you the ability to automatically discover and adapt to changes in DynamoDB tables. All details are provided.
Is Flink SQL a Database? | Apache Flink SQL
Apache Flink SQL has a lot in common with SQL databases, but in several fundamental ways it’s actually quite different. Learn how Apache Flink has adapted concepts like queries, materialized views, catalogs, and ACID guarantees from SQL databases to fit into the world of stream processing.
How to work with a paused stream | Apache Flink in Action
Using Apache Flink watermarks can create havoc when you have a stream that has significant delays between records. In this video we’ll talk about a possible solution to this situation using a batch close record, which will ensure that your data is up to date.
Handling the Producer Request: Kafka Producer and Consumer Internals, Part 2
Welcome to the second installment of our blog series to understand the inner workings of the beautiful black box that is Apache Kafka. We’re diving headfirst into Kafka to see how we actually interact with the cluster through producers and consumers. Along the way, we explore the configurations that affect each step of this epic journey and the metrics that we can use to more effectively monitor the process.
How to source data from AWS DynamoDB to Confluent using Kinesis Data Streams and Connect
This is a one-minute video showing an animated architectural diagram of an integration between Amazon DynamoDB and Confluent Cloud using Kinesis Data Streams and the Kinesis Data Streams connector. It’s a fully managed and serverless solution that reduces operational complexity and leverages scalability and cost-effectiveness.