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Managing 238M Memberships at Netflix
In this article Surabhi Diwan shared how the Netflix membership team does distributed systems: the architecture bets, technology choices, and operational semantics that serve the needs of Netflix’s ever-growing member base.
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Banking on Thousands of Microservices
Lessons learned building a banking platform, starting from technological choices like using Cassandra and Kubernetes in the early days to maintain the speed of execution through platform engineering and developer experience. With some mistakes and incidents along the way.
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Why a Serverless Data API Might Be Your Next Database
In this article, author Pieter Humphrey discussed database as a service (DBaaS) and serverless data API for cloud based data management.
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Beyond the Database, and beyond the Stream Processor: What's the Next Step for Data Management?
Databases have been around forever with the same shape: you make a request to your data and then you receive an answer. Now, stream processors came along with a different approach: data isn’t locked up, it is in motion. Understand how stream processors and databases relate and why there is an emerging new category of databases that focus on data that stays in place as well as data that moves.
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How to Use Open Source Prometheus to Monitor Applications at Scale
In this article, the author discusses how to collect metrics and achieve anomaly detection from streaming data using Prometheus, Apache Kafka and Apache Cassandra technologies.
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Polyglot Persistence Powering Microservices
At Netflix, the cloud database engineering team is responsible for providing several flavors of data persistence as a service to microservice development teams. Roopa Tangirala explained how her team has created self-service tools that help developers easily implement the appropriate data store for each project's needs.
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Cassandra: The Definitive Guide, 2nd Edition Book Review and Interview
Cassandra: The Definitive Guide, 2nd Edition book authored by Jeff Carpenter and Eben Hewitt covers the Cassandra NoSQL database version 3.0. Authors discuss several different important topics related to this popular database, including data modeling and Cassandra architecture. InfoQ spoke with Jeff Carpenter about the book and Cassandra database current features and future roadmap.
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From Raw Data to Data Science: Adding Structure to Unstructured Data to Support Product Development
With unstructured database technologies like Cassandra, MongoDB and even JSON storage in Postgres, unstructured data has become remarkably easy to store and to process. Software and data engineers alike can succeed in a world (mostly) free from data modelling, which is no longer a prerequisite to collecting data or extracting value from it.
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Chris Fregly on the PANCAKE STACK Workshop and Data Pipelines
InfoQ Interviews Chris Fregly, organizer for the 4000+ member Advanced Spark and TensorFlow Meetup about the PANCAKE STACK workshop, Spark and building data pipelines for a machine learning pipeline
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Virtual Panel: Current State of NoSQL Databases
NoSQL databases have been around for several years now and have become a choice of data storage for managing semi-structured and unstructured data. These databases offer lot of advantages in terms of linear scalability and better performance for both data writes and reads. InfoQ spoke with four panelists to get different perspectives on the current state of NoSQL databases.
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Martin Van Ryswyk on DataStax Enterprise Graph Database
DataStax recently announced a new product called DataStax Graph to store graph data models. It's based on open source Titan graph database and uses Apache Tinkerpop framework's Gremlin query language. InfoQ spoke with Martin Van Ryswyk about the new product.
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Practical Cassandra: A Developer's Approach - Book Review and Interview
Practical Cassandra: A Developer's Approach book by Russell Bradberry and Eric Lubow, is a developer's guide to build applications using Cassandra NoSQL database. InfoQ spoke with the authors about the book, Cassandra data model, design considerations and how Cassandra performs concurrency and versioning of the data sets.