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Unravel Data Adds Native Support for Impala and Kafka

Unravel Data, the Application Performance Management (APM) platform designed for Big Data, announced that it has integrated support for Cloudera Impala and Apache Kafka into its platform, allowing users to derive the maximum value from those applications. Unravel continues to offer the only full-stack solution that doesn’t just monitor and unify system-level data, but rather tracks, correlates, and interprets performance data across the full-stack in order to optimize, troubleshoot, and analyze from a single pane.

Databricks Simplifies and Scales Deep Learning with New Apache Spark Library

Databricks, the company founded by the creators of the popular Apache Spark project, announced Deep Learning Pipelines, a new library to integrate and scale out deep learning in Apache Spark.

The Definitive Guide to Evaluating Cloud-based Apache Spark Platforms

This guide is designed to help you focus on your overall company goals. Do you want to build and manage your own Spark environment or leverage the best possible choice on the market? Find a solution you can use as an effective tool for the real work of getting business value from big data analytics. To learn more download this definitive guide to evaluating cloud-based Apache Spark platforms.

Cloudera Launches Altus to Simplify Big Data Workloads in the Cloud

Cloudera, Inc, (NYSE:CLDR) the provider of a leading modern platform for machine learning and advanced analytics, announced the release of Cloudera Altus, a Platform-as-a-Service (PaaS) offering that makes it easier to run large-scale data processing applications on public cloud.

Hadoop, Spark or Both?

In this contributed article, tech writer Blake Davies asks the question: Spark or Hadoop? This question has recently sparked various discussions throughout the online communities. Even though these two work on different principles, they can be applied in a same way for various uses. While Hadoop is a household name in the world of big data processing, Spark is still building a name for itself and it’s doing so with “style”.

Pepperdata® Code Analyzer for Apache Spark Highlights Performance Bottlenecks for Developers

Pepperdata, the DevOps for Big Data company, announced Pepperdata Code Analyzer for Apache Spark, which provides Spark application developers the ability to identify performance issues and connect them to particular blocks of code within an application. Code Analyzer is a new product that follows on the heels of Pepperdata Application Profiler, which provides Hadoop and Spark developers with actionable recommendations for improving job performance.

MapR Releases New Ecosystem Pack with Optimized Security and Performance for Apache Spark

MapR Technologies, Inc., the provider of the Converged Data Platform that converges the essential data management and application processing technologies on a single, horizontally scalable platform, announced its next major release of the MapR Ecosystem Pack (MEP) program. MEP is a broad set of open source ecosystem projects that enable big data applications running on the MapR Converged Data Platform with inter-project compatibility.

Databricks Launches New Edition of Its Spark-Based Cloud Platform for Data Engineers

Databricks, the company founded by the creators of the popular Apache Spark project and providers of the leading Spark-based cloud platform for data science, announced an edition of its cloud platform optimized specifically for data engineering workloads called Databricks for Data Engineering.

Impetus Technologies Announces StreamAnalytix 3.0 Featuring Support for Apache Spark-Based Batch Processing

Impetus Technologies, a big data thought leader and software solutions company, announced StreamAnalytix™ 3.0 featuring support for Apache Spark-based batch processing and enriched online and offline machine learning features, helping enterprises maximize the performance of their analytical models and achieve the most favorable business outcomes. The newest version adds to the stream processing capabilities driven […]

Data as a Critical Element in the Discovery and Delivery of Smart Energy

In this contributed article, Jules S. Damji, an Apache Spark Community Evangelist with Databricks, shows how as the value of data continues to grow, the next-generation smart grid should become a reality, benefiting utility companies and consumers alike.