Systems | Development | Analytics | API | Testing

With the GA of Apache Spark stored procedures in BigQuery, users can extend their queries with Spark-based data processing via BigQuery APIs.

Many companies talk about cloud integration in a theoretical way. But cloud technologies aren’t theoretical. They’re a rapidly growing segment of technology that’s changing the way businesses operate. In the following article, we move from theory to practice so you can have a more realistic vision of what to expect when you move more of your on-site tech to the cloud.

We’re excited to talk about our vision for Tableflow, which makes it push-button simple to take Apache Kafka® data and feed it directly into your data lake, warehouse, or analytics engine as Apache Iceberg® tables. Making operational data accessible to the analytical world is traditionally a complex, expensive, and brittle process and we believe we can do better to unify the operational and analytical estates.

Last year, we announced our plan to build a cloud-native Apache Flink® service to meet the growing demand for scalable and efficient stream processing solutions in the cloud. Today, we're thrilled to announce the general availability of Confluent Cloud for Apache Flink across all three major clouds. This means that you can now experience Apache Kafka® and Flink as a unified, enterprise-grade platform to connect and process your data in real time, wherever you need it.

We’re excited to share the latest and greatest features on Confluent Cloud, in our first launch of 2024. This Cloud Launch comes to you from Kafka Summit London, where we talked about the latest updates highlighted in our launch, including serverless Apache Flink®, some exciting pricing changes, updates to connectors, and more! We also shared our vision for a future offering, Tableflow.

The editorial team of Hitachi Vantara sat down for an interview with our Chief Product Officer, Octavian Tanase, to learn about his vision and strategy for AI in the enterprise.

A Smartsheet report found that over 40% of workers spend at least a quarter of their workweek manually extracting data. Tax specialists in many organizations spend hours or even days sorting through piles of paper or PDF documents, looking for relevant information, and entering it into spreadsheets or databases. That’s a lot of time and money wasted on a tedious and error-prone process. Fortunately, there is a better way to handle tax form data extraction.