September 2018
InfoQ

Data Engineering Special Report

Sponsored by
Hazelcast
Latest Content, Top Viewed Content, News, Top Articles, Top Presentations
 
In this special newsletter we bring you up to date on all the new content and news related to Data Engineering on InfoQ. We are also maintaining a portal page for this content on InfoQ at: https://www.infoq.com/ai-ml-data-eng.
How to Choose a Stream Processor for Your App (articles, Aug 21, 2018)
NATS Messaging System Gets Kafka-Like Log API via Liftbridge (news, Aug 20, 2018)
Engineering Systems for Real-Time Predictions @DoorDash (presentations, Aug 22, 2018)
ML Data Pipelines for Real-Time Fraud Prevention @PayPal (presentations, Aug 22, 2018)

Caching Strategies Explained

This white paper delves into different cache types, strategies, and topologies. It examines eviction strategies, Java temporary caching using the JCache API, and introduces Hazelcast IMDG caching. Download now.

Sponsored content

Caching Strategies Explained
Democratizing Stream Processing with Apache Kafka and KSQL (articles, Jun 15, 2018)
Analyzing & Preventing Unconscious Bias in Machine Learning (presentations, Jun 12, 2018)
Experiences from Building an Event-Sourced System with Kafka Streams (news, Jul 05, 2018)

Apple Has Released Core ML 2

At WWDC Apple released Core ML 2: a new version of their machine learning SDK for iOS devices. The new release of Core ML should create an inference time speedup of 30% for apps developed using Core ML 2. An important new feature of the Core ML SDK is Create ML. Developers can create and train custom machine learning models on their mac.

Google Brings Machine Learning to Firebase with ML Kit

Google recently introduced ML Kit, a machine-learning module fully integrated in its Firebase mobile development platform and available for both iOS and Android. With this new Firebase module, Google simplifies the creation of machine-learning powered applications on mobile phones and solves some of the challenges of implementing computationally intense features on mobile devices.

A Reference Guide to Stream Processing

This white paper introduces the domain of stream processing, covering use cases, the building blocks of a stream processing solution, and key concepts used when building a streaming pipeline such as: definition of the dataflow, keyed aggregation, windowing. Download now.

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A Reference Guide to Stream Processing

Flutter Release Preview 1 Supports ML Kit and More

Google recently announced Flutter Release Preview 1. Flutter is an open-source framework for cross-platform app development for both iOS and Android. Flutter Release Preview 1 includes support for hardware keyboards and barcode scanners, video recording, ML Kit, an update to the Flutter extension for Visual Studio Code, and more.

Distributed Messaging Framework Apache Pulsar 2.0 Supports Schema Registry and Topic Compaction

The latest version of open-source distributed pub-sub messaging framework Apache Pulsar enables companies to move “beyond batch” by acting on data in motion. Streamlio recently announced the availability of Apache Pulsar 2.0 streaming messaging solution. The new version supports Pulsar Functions, Schema Registry and Topic Compaction.

Is Batch ETL Dead, and is Apache Kafka the Future of Data Processing?

At QCon San Francisco 2016, Neha Narkhede presented “ETL is Dead; Long Live Streams”, and discussed the changing landscape of enterprise data processing.

The InfoQ eMag: Real-World Machine Learning: Case Studies, Techniques and Risks

Machine learning & deep-learning brought data analytics to the developer community. The eMag focuses on the current landscape of ML technologies and presents several associated real-world case studies.

Columnar Databases and Vectorization

In this article, author Siddharth Teotia discusses the Dremio database which is based on Apache Arrow with vectorization capabilities.

A Critique of Resizable Hash Tables: Riak Core & Random Slicing

This fall, Wallaroo Labs will be releasing a large new feature set to our distributed data stream processing framework, Wallaroo.

Getting Started with Microservices using Hazelcast IMDG and Spring Boot

Learn how Spring Boot and Hazelcast IMDG contribute to the microservices landscape, enhancing the benefits and alleviating some of the common downsides of implementing microservices. Download now.

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etting Started with Microservices using Hazelcast IMDG and Spring Boot

End-to-End ML without a Data Scientist

Holden Karau discusses how to train models, and how to serve them, including basic validation techniques, A/B tests, and the importance of keeping models up-to-date.

CRDTs and the Quest for Distributed Consistency

Martin Kleppmann explores how to ensure data consistency in distributed systems, especially in systems that don't have an authoritative leader, and peer-to-peer communication.

The Future of Distributed Databases Is Relational

Sumedh Pathak talks about his team’s journey to create a more modern relational database, distributed systems, scaling Postgres, distributed query planner and the distributed deadlock detection.
 

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