Learn how we prioritize privacy and data protection with a robust framework that adheres to the GDPR and other global regulations.

I’m excited to announce that Confluent has acquired WarpStream, an innovative Kafka-compatible streaming solution with a unique architecture. We’re excited to be adding their product to our portfolio alongside Confluent Platform and Confluent Cloud to serve customers who want a cloud-native streaming offering in their own cloud account.

Imagine a multinational business that deals with multiple suppliers and customers scattered across the globe, each with their own systems and processes. How does it ensure smooth communication and transactions with its business partners? The answer is Electronic Data Interchange (EDI), a standardized method for exchanging electronic documents between businesses.

What is data fabric architecture? The case for data fabric 4 key facts about data fabric architecture Data fabric architecture can modernize and future-proof your data approach Data fabric architecture is a virtual data layer that connects any number of external systems together to provide unified access and a complete, 360-degree view of an organization’s data. Whether your data lives in legacy systems or multi-cloud environments, a data fabric can connect these systems together for a unified view.

Data elements are the fundamental building blocks of EDI documents. They represent individual information within a transaction set, such as city, state, country, item number, quantity, and price. Each data element is defined by its data type, which specifies whether it’s numeric, alphanumeric, a date, or a time. Additionally, the definition includes details like minimum and maximum length requirements and any applicable code values.

Oracle SQL Developer is a powerful tool widely used by data professionals for managing and interacting with Oracle databases. One of the common tasks that data analysts in mid-market companies frequently encounter is the need to export data from Oracle SQL Developer to Excel for further analysis, reporting, or sharing. This blog will provide a detailed, step-by-step guide on how to achieve this, ensuring that every method is covered comprehensively, catering to various user needs and preferences.

In just 12 short months, the Connect with Confluent (CwC) technology partner program has transformed from a new, ambitious initiative to expand the data streaming ecosystem into a thriving portfolio that’s rapidly increasing the breadth and value of real-time data. The program now provides a portfolio of 50+ integrations, each one amplifying the capabilities of Confluent's unified data streaming platform for Apache Kafka and Apache Flink.

I shouldn’t have to convince anyone that Apache Kafka is an incredibly useful and powerful technology. As a distributed event streaming platform, it’s adept at storing your event data and serving it up for downstream consuming applications to make sense of that information––in real time or as close to real time as your use case permits. The real beauty of Kafka as a technology is that it can do it with very little effort on your part. In effect, it’s a black box.