InfoQ Homepage Key-Value Store Content on InfoQ
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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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Distributed Transactions at Scale in Amazon DynamoDB
Amazon DynamoDB supports transactions without sacrificing performance or availability. Akshat Vig explains how DynamoDB introduced TransactGetItems and TransactWriteItems for atomic operations, proving full ACID support in distributed transactions.
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Designing the Jit Analytics Architecture for Scale and Reuse
As a SaaS provider, analytical data at Jit needs to be useful to both their customers and to internal stakeholders. AWS services including EventBridge, Kinesis Data Firehose, and Timestream handle data ingestion and UI platforms from Mixpanel and Segment provide data visualization.
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DynamoDB Data Transformation Safety: from Manual Toil to Automated and Open Source
Data transformation remains a continuous challenge in engineering and built upon manual toil. The open source utility Dynamo Data Transform was built to simplify and build safety and guardrails into data transformation for DynamoDB based systems––built upon a robust manual framework that was then automated and open sourced. This article discusses the challenges with Data Transformation.
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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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Understanding Serverless: Tips and Resources for Building Servicefull Applications
There are still many misconceptions and concerns regarding serverless solutions. Vendor lock-in, tooling, cost management, cold starts, monitoring and the development lifecycle are all hot topics where serverless technologies are concerned. This article shares tips and resources to guide serverless newcomers towards building powerful, flexible and cost-effective serverless applications.
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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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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. One of the new features requires a size-adjustable, distributed data structure to support growing & shrinking of compute clusters. It might be a good idea to use a distributed hash table to support the new feature, but what distributed hash algorithm should we choose?
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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