Apr 8 · 13 min read · What Kafka Streams Is (and Is Not) Kafka Streams is a client library, not a service. That distinction matters more than almost anything else in this comparison. When you use Kafka Streams, you write Java or Kotlin code that imports the Kafka Streams ...
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Apr 7 · 16 min read · In the Apache Flink vs RisingWave real-time analytics benchmark using the Nexmark suite, RisingWave outperforms Flink on 22 of 27 queries, often by a factor of 2x to 10x. The largest gains appear on aggregation-heavy queries, where RisingWave's incre...
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Apr 2 · 10 min read · Every e-commerce platform has some version of this pipeline: orders land in a Kafka topic, you enrich each one with product details from a catalog table, and the result feeds a dashboard, a feature store, or a downstream sink. The join looks trivial ...
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Apr 2 · 14 min read · Every modern application generates a constant stream of data: user clicks, transactions, sensor readings, log events. Traditional databases were designed for a world where data arrives in batches and queries run on demand. But when you need answers a...
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Apr 2 · 12 min read · Why This Comparison Matters in 2026 You need to process data the moment it arrives. Whether you are building fraud detection, real-time dashboards, or CDC pipelines, choosing the wrong stream processing platform can cost months of engineering time an...
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Mar 31 · 13 min read · If you have worked with traditional databases, you know the pattern: data lands in tables, and you run queries against it when you need answers. The database does all the heavy lifting at read time, scanning rows, joining tables, and computing aggreg...
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Mar 28 · 20 min read · TLDR: Kappa architecture replaces Lambda's batch + speed dual codebases with a single streaming pipeline backed by a replayable Kafka log. Reprocessing becomes replaying from offset 0. One codebase, no drift. TLDR: Kappa is the right call when your t...
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Mar 28 · 18 min read · TLDR: Apache Spark distributes Python DataFrame jobs across a cluster of executors, using lazy evaluation and the Catalyst query optimizer to process terabytes with the same code that works on gigabytes. Master partitioning, shuffle-awareness, and St...
Join discussionMar 13 · 14 min read · TLDR: Stream pipelines succeed when event-time semantics, state management, and replay strategy are designed together — and Kafka Streams lets you build all three directly inside your Spring Boot service. Stripe's real-time fraud detection processes...
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