In industries relying on up-to-the-minute insights, interruptions disrupt crucial processes, hindering timely responses to market changes and the accuracy of analytical outcomes. This can lead to ...

Discover the best cloud ETL tools for data engineers in 2025. Compare features, pricing, and use cases as we explore the most effective data integration solutions for modern organizations with ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Navigating vast data sets and ensuring they’re ready for use is a daunting task for many companies. ETL solutions have redefined this process, providing a way to make sense of data at any scale and ...

Using workarounds to pipe data between systems carries a high price and untrustworthy data. Bharath Chari shares three possible solutions backed up by real use cases to get data streaming pipelines ...

As the volume, velocity, and variety of data continue to accelerate, developers are facing a critical shift: data is no longer just stored and queried--it's constantly on the move. From traditional ...

Data is the most valuable asset for modern businesses. For any organization to extract valuable insights from data, that data needs to flow freely in a secure and timely manner across its different ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire Apache ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...