Category Archives: Cloudera Navigator

Best Practices for Enterprise Data Hub Encryption

Categories: Cloudera Navigator Platform Security & Cybersecurity

Encryption is a key security feature in Cloudera-powered enterprise data hubs (EDHs). This post explains some best practices for deployment of Cloudera Navigator Encrypt for that purpose.

For those unfamiliar with the product, Cloudera Navigator Encrypt provides scalable, high-performance encryption for critical Apache Hadoop data. It utilizes industry-standard AES-256 encryption and provides a transparent layer between the application and filesystem. Cloudera Navigator Encrypt also includes process-based access controls, allowing authorized processes to access encrypted data while simultaneously preventing admins or super-users like root from accessing data that they don’t need to see.

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Cloudera Enterprise 5.7 is Released

Categories: CDH Cloudera Manager Cloudera Navigator Hive Spark

Cloudera Enterprise 5.7 is now generally available (comprising CDH 5.7, Cloudera Manager 5.7, and Cloudera Navigator 2.6).

Cloudera is excited to announce the general availability of Cloudera Enterprise 5.7! Main highlights of this release include production-ready Hive-on-Spark functionality, which will help users accelerate their use of Apache Spark as a data processing standard; 4x performance gains for Apache Impala (incubating); easier cluster configuration and utilization reporting; and end-to-end encryption for Apache Spark data.

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Introducing Cloudera Navigator Optimizer: For Optimal SQL Workload Efficiency on Apache Hadoop

Categories: Cloudera Navigator Impala Performance

Cloudera Navigator Optimizer, a new (beta) component of Cloudera Enterprise, helps optimize inefficient query workloads for best results on Apache Hadoop.

With the proliferation of Apache Hadoop deployments, more and more customers are looking to reduce operational overheads in their enterprise data warehouse (EDW) installations by exploiting low-cost, highly scalable, open source SQL-on-Hadoop frameworks such as Impala and Apache Hive. Processing portions of SQL workloads better suited to Hadoop on these frameworks,

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