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Databricks Secures $140 Million to Accelerate Analytics and Artificial Intelligence in the Enterprise

Databricks, provider of the leading Unified Analytics Platform and founded by the team who created Apache Spark™, announced it has secured $140 million in a Series D funding round led by Andreessen Horowitz. New Enterprise Associates and Battery Ventures also participated.

Interview: Ash Munshi, CEO at Pepperdata

I recently caught up with Ash Munshi, CEO at Pepperdata, to get a rundown on his company, a sense for how big data and DevOps are related, some highlights on new product offerings, and his sense for where Pepperdata is headed in the future.

IBM Combines All-Flash and Storage Software Optimized for Hortonworks

IBM (NYSE: IBM) announced a new all-flash, high-performance data and file management solution for enterprise clients running exabyte-scale big data analytics, cognitive and AI applications. The combined flash and storage software solution has been certified with the Hortonworks Data Platform (HDP) to provide clients with more choice in selecting the right platform for their big data analytics on data processing engines like Hadoop and Spark.

GigaSpaces Launches InsightEdge 2.1 to Accelerate Insight-Driven Transformation

GigaSpaces, a leading provider of in-memory computing (IMC) platforms, has upgraded InsightEdge, a Hybrid Transactional and Analytical Processing platform, to support Apache Spark 2.1. InsightEdge leverages Spark and GigaSpaces’ open source IMC data grid, provides a mission critical distributed RAM/SSD/SCM data store.

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.

Impetus Technologies Unveils New, TensorFlow-Based Deep Learning Feature on Apache Spark for StreamAnalytix

Impetus Technologies, a big data software products and services company, announced integration of a new, deep learning capability for its StreamAnalytix™ platform. Based on the TensorFlow™ open source software library for machine learning, this new capability demonstration showcases an image recognition application running on an Apache Spark Streaming pipeline on StreamAnalytix.

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.

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.