Welcome to the DataStax Developer Blog. Here’s where you can find the latest insights and technical articles from top experts and fellow peers on distributed systems, data management strategies, Star Wars/Star Trek debates, and best practices for building cloud applications that are always on, built with effortless scale, and deliver instant insight.

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From CFS to DSEFS

By Piotr Kołaczkowski - May 23, 2017

Cassandra File System (CFS) is the default distributed file system in the DataStax Enterprise platform in versions 2.0 to 5.0. Its primary purpose is to support Hadoop and Spark workloads with temporary Hadoop-compatible storage. In DSE 5.1, CFS has been deprecated and replaced with a much improved DataStax Enterprise File System (DSEFS). DSEFS is available as an option in DSE 5.0, and was made the default distributed file system in DSE 5.1.

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DataStax Drivers Fluent APIs for DSE Graph are out!

By Kevin Gallardo - May 16, 2017

Following the DataStax Enterprise 5.1 release, DataStax released its first non-beta versions of the Fluent APIs for DSE Graph. This new feature brings the DataStax Enterprise Drivers into full compatibility with the Apache TinkerPop GLVs, and we even included additional functionalities in order to make the experience of developing graph applications even faster and easier.

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DSE 5.1: Automatic Optimization of Spark SQL Queries Using DSE Search

By Russell Spitzer - May 9, 2017

DSE Search (Apache Solr based) and DSE Analytics (Apache Spark Based) may seem like they are basically designed for orthogonal use cases. Search optimizes the quick generic searches over your Big Data and Analytics optimizes for reading your entire dataset for processing. But there is a sweet spot where Analytics can benefit greatly from the enhanced indexing capabilities from Search. Previously in DSE this synergy could only be accessed from the RDD api but now with DSE 5.1 we bring DSE Search together with Dse Analytics in SparkSQL and DataFrames.

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Introducing DSE Graph Frames

By Artem Aliev - May 2, 2017

The DseGraphFrame package provides the Spark base API for bulk operations and analytics on Dse Graph. It is inspired by Databricks’ GraphFrame library and supports a subset of Apache TinkerPop Gremlin graph traversal language. It supports reading of DSE Graph data into a GraphFrame and writing GraphFrames from any format supported by Spark into DSE Graph.

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DSE Continuous Paging Tuning and Support Guide

By Russell Spitzer - April 25, 2017

Continuous paging (CP) is a new method of streaming bulk amounts of records from Datastax Enterprise to the Datastax Java Driver. This is disabled by default and can be activated and used only when running with DataStax Enterprise (DSE) 5.1. When activated, all read operations executed from the CassandraTableScanRDD will use continuous paging. Continuous Paging is an Opt-In feature and can be enabled as a Spark configuration option.

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Property Graph Algorithms

By Marko A. Rodriguez - April 10, 2017

The term property graph has come to denote an attributed, multi-relational graph. That is, a graph where the edges are labeled and both vertices and edges can have any number of key/value properties associated with them.

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Webinar Q&A Follow-up – DataStax Enterprise 5.1: 3X the operational analytics speed, help for multi-tenant SaaS apps, & other shiny things

By Gehrig Kunz - March 24, 2017

In this week's webinar, DataStax Enterprise 5.1: 3X the operational analytics speed, help for multi-tenant SaaS apps, & other shiny things, our awesome Technical Evangelist, David Gilardi and I had the opportunity to give a sneak peek at what's in store in our upcoming April 4th release of DataStax Enterprise 5.1, DataStax OpsCenter 6.1, and DataStax Studio 2.0. Here are the answers to your webinar questions.

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Getting the Hang of Using the DataStax Graph Loader: The Basics 

By Marc Selwan - March 21, 2017

The DataStax Graph Loader is an important tool in the development of a DataStax Graph use case. While its primary function is to bulk load data into DSE Graph, it can be a great tool to help you familiarize yourself with some of the in's and out's (pun intended) of the DSE Graph.

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