Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Senyo Simpson discusses how Rust's core ...

Google is promising a single notebook environment for machine learning and data analytics, integrating SQL, Python, and ...

Databricks Inc., the primary commercial steward behind the popular open source Apache Spark data processing framework for Big Data analytics, published a new report indicating the technology is still ...

Apache Spark 3.0 is now here, and it’s bringing a host of enhancements across its diverse range of capabilities. The headliner is an big bump in performance for the SQL engine and better coverage of ...

For data engineers looking to leverage Apache Spark™'s immense growth to build faster and more reliable data pipelines, Databricks is happy to provide The Data Engineer's Guide to Apache Spark. This ...

It's time to celebrate the incredible women leading the way in AI! Nominate your inspiring leaders for VentureBeat’s Women in AI Awards today before June 18. Learn More Following the initial rise of ...

Hadoop, the data processing framework that’s become a platform unto itself, is only as good as the components that plug into it. But the conventional MapReduce component for Hadoop has a reputation ...

Apache Spark rose to prominence within the Hadoop world as a faster and easier to use alternative to MapReduce. But as fast as Spark is today, it won’t hold a candle to future versions of Spark that ...

Reactive programming company Typesafe today released a survey that confirms the high adoption rate of Apache Spark, an open source Big Data processing framework that improves traditional Hadoop-based ...

Apache Spark, the extremely popular data analytics execution engine, was initially released in 2012. It wasn’t until 2015 that Spark really saw an uptick in support, but by November 2015, Spark saw 50 ...