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Reactive Real-Time Notifications with SSE, Spring Boot, and Redis Pub/Sub
Explore the power of reactive programming for building scalable real-time notification systems. Using Spring Boot Reactive and Spring WebFlux, leverage non-blocking operations to handle high-volume, asynchronous data flows efficiently. Discover how Redis Pub/Sub enables event-driven messaging and how the SSE protocol provides persistent connections for instant client updates without polling.
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How to Use Redis TimeSeries with Grafana for Real-Time Analytics
In this article, author Roshan Kumar discusses how a purpose-built database like RedisTimeSeries can be used to manage time-series data. He also shows how to visualize this data in a Grafana dashboard.
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Postgres Handles More Than You Think
Thinking about scaling beyond Postgres with a data store like Redis or Elasticsearch? Think again before adopting a complex infrastructure. Postgres can scale for heavy loads and offers powerful features which are not obvious at first sight. For example, it's possible to enable in-memory caching, text search, specialized indexing, and key-value storage. Article
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Real-Time Data Processing Using Redis Streams and Apache Spark Structured Streaming
Structured Streaming, introduced with Apache Spark 2.0, delivers a SQL-like interface for streaming data. Redis Streams enables Redis to consume, hold and distribute streaming data between multiple producers and consumers. In this article, author Roshan Kumar walks us through how to process streaming data in real time using Redis and Apache Spark Streaming technologies.
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Challenges of Building a Reliable Realtime Chat Service
Realtime chat has become a common feature of modern applications. These days not only communicators and social networks allow users to talk with each other over the Internet—chat is crucial in healthcare, e-commerce, gaming and many other industries.
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Picking an Active-Active Geo Distribution Strategy: Comparing Merge Replication and CRDT
Modern distributed applications are fuelling the growing demand for distributed active-active, multi-master databases. While most popular databases support multi-master deployment, different databases employ different techniques. LWW, MVCC, merge replication and CRDTs deliver eventual consistency, offering read and write access with local latency and remaining available during network partitions.
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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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Using Redis as a Time Series Database: Why and How
In this article, Dr. Josiah Carlson, author of the book “Redis in Action”, explains how to use Redis and sorted sets with hashes for time series analysis.
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Jepsen: Testing the Partition Tolerance of PostgreSQL, Redis, MongoDB and Riak
Distributed systems are characterized by exchanging state over high-latency or unreliable links. The system must be robust to both node and network failure if it is to operate reliably--however, not all systems satisfy the safety invariants we'd like. In this article, we'll explore some of the design considerations of distributed databases, and how they respond to network partitions.
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Interview and Book Review: The LogStash Book, Log Management Made Easy
James Turnbull makes a compelling case for using Logstash for centralizing logging by explaining the implementation details of Logstash within the context of a logging project. The book targets both small companies and large enterprises through a two sided case; both for the low barrier to entry and the scaling capabilities.