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Couchbase 4.6 Developer Preview Released, Adds Real-Time Connectors for Apache Spark 2.0 and Kafka

by Alexandre Rodrigues on  Nov 28, 2016

Couchbase 4.6 Developer Preview features full text search improvements, cross data center replication with globally-ordered conflict resolution and connectors for real-time analytics technologies: one for Spark 2.0 and the other for Kafka.

Spark Summit EU Highlights: TensorFlow, Structured Streaming and GPU Hardware Acceleration

by Alexandre Rodrigues on  Nov 13, 2016

Apache Spark integration with deep learning library TensorFlow, online learning using Structured Streaming and GPU hardware acceleration were the highlights of Spark Summit EU 2016 held last week in Brussels.

Microsoft Releases Data Science Tools for Interactive Data Exploration and Modeling

by Srini Penchikala on  Nov 07, 2016

Microsoft recently released two new data science tools for interactive data exploration: modeling and reporting. These tools can be reused by data science teams with data specific tasks in their projects. The goal is to ensure consistency and completeness of data science tasks across different projects in the organization.

Microservices and Stream Processing Architecture at Zalando Using Apache Flink

by Srini Penchikala on  Oct 31, 2016 1

Javier Lopez and Mihail Vieru spoke at Reactive Summit 2016 Conference about cloud-based data integration and distribution platform used for stream processing in business intelligence use cases. Their solution is based on technologies such as Flink, Kafka and Elasticsearch.

Wolfram Wants to Deliver “Computation Everywhere” with New Private Cloud

by Richard Seroter on  Oct 26, 2016

Wolfram, the software company behind computation-centric products like Mathematica and Wolfram|Alpha, shipped a new private cloud appliance targeting companies that want to centralize their computational efforts.

Stream Processing and Lambda Architecture Challenges

by Alexandre Rodrigues on  Oct 19, 2016 4

Lambda architecture has been a popular solution that combines batch and stream processing. Kartik Paramasivam at LinkedIn wrote about how his team addressed stream processing and Lambda architecture challenges using Apache Samza for data processing. The challenges described are the late arrival of events and the processing of duplicated messages.

Jay Kreps on Distributed Stream Processing with Apache Kafka and Kafka Streams

by Srini Penchikala on  Oct 16, 2016

Apache Kafka and Kafka Streams frameworks help with developing stream-centric architectures and distributed stream processing applications. Jay Kreps, CEO of Confluent, gave the keynote presentation on stream processing and microservices at Reactive Summit 2016 Conference last week.

Reactive Summit 2016 Conference: Reactive Microservices and Staging Data Pipelines

by Srini Penchikala on  Oct 08, 2016

Reactive microservices, data center scale operating system (DCOS), and staging reactive data pipelines were the highlighted topics at Reactive Summit 2016 Conference held this week. InfoQ team attended the conference and this post is a summary of the first day's events at the conference.

Confluent Announces Kafka for the Enterprise with Multi-Datacenter Replication

by Srini Penchikala on  Oct 05, 2016

Confluent Enterprise latest version supports multi-datacenter replication, automatic data balancing, and cloud migration capability. Confluent, provider of the Apache Kafka based streaming platform, announced last week the new features for Confluent Enterprise, to help build streaming data pipelines and develop stream processing applications.

Amazon Kinesis Analytics is Like SaaS for Big Data Analysis

by Elton Stoneman on  Sep 14, 2016

Real-time analysis of event streams has a new focus in Big Data platforms, both on-premise and in the cloud. AWS have released Amazon Kinesis Analytics, a rival to Azure StreamAnalytics. Both platforms use a simple SQL language for complex querying, and move Big Data analysis into a SaaS-like space.

IBM Creates Artificial Neurons from Phase Change Memory for Cognitive Computing

by Srini Penchikala on  Sep 13, 2016

A team of scientists at IBM Research in Zurich, have created an artificial version of neurons using phase-change materials to store and process data. These phase change based artificial neurons can be used to detect patterns and discover correlations in Big Data (real-time streams of event based data) and unsupervised machine learning at high speeds using very little energy.

Getting the Data Needed for Data Science

by Ben Linders on  Sep 02, 2016

Data science is about the data that you need; deciding which data to collect, create, or keep is fundamental argues Lukas Vermeer, an experienced Data Science professional and Product Owner for Experimentation at Booking.com. True innovation starts with asking big questions, then it becomes apparent which data is needed to find the answers you seek.

Azure Premium Messaging Service Reaches General Availability

by Kent Weare on  Jul 31, 2016

On July 15th, Microsoft announced the Azure Premium Messaging service has reached General Availability (GA). Premium Messaging targets customers who would like more predictable messaging performance. InfoQ reached out to Dan Rosanova, Principal Program Manager on the Azure Service Bus team for additional insight into this milestone.

Basho Open Sources Time Series Database Riak TS 1.3

by Rags Srinivas on  Jul 15, 2016

InfoQ's Rags Srinivas talks to Basho's CTO Dave McCrory about the open sourcing of Riak TS 1.3 which is geared to handle time series data.

Meson Workflow Orchestration and Scheduling Framework for Netflix Recommendations

by Srini Penchikala on  Jul 10, 2016

Netflix's goal is to predict what you want to watch before you watch it. They do this by running a number of machine learning (ML) workflows every day. Meson is a workflow orchestration and scheduling framework that manages the lifecycle of all these machine learning pipelines that build, train and validate personalization algorithms to help with the video recommendations.

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