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    <title>event-stream</title>
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    <updated>2026-06-14T15:16:27+00:00</updated>
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            <entry>
            <id>https://links.biapy.com/links/10426</id>
            <title type="text"><![CDATA[RisingWave]]></title>
            <link rel="alternate" href="https://risingwave.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10426"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Real-Time Event Streaming Platform.
Streaming CDC, stream processing, low-latency serving, and Iceberg management. 

RisingWave is a real-time event streaming platform designed to offer the simplest and most cost-effective way to process, analyze, and manage real-time event data — with built-in support for the Apache Iceberg™ open table format. It provides both a Postgres-compatible SQL interface and a DataFrame-style Python interface.

RisingWave can ingest millions of events per second, continuously join and analyze live streams with historical data, serve ad-hoc queries at low latency, and persist fresh, consistent results to Apache Iceberg™ or any other downstream system.

- [RisingWave @ GitHub](https://github.com/risingwavelabs/risingwave).

Related contents:

- [The Case for Hybrid Cache for Object Stores @ Data Engineer Things&amp;#039; Medium](https://blog.dataengineerthings.org/the-case-for-hybrid-cache-for-object-stores-4b1f02ec6c9a).
- [You Gotta Push If You Wanna Pull @ Gunnar Morling](https://www.morling.dev/blog/you-gotta-push-if-you-wanna-pull/).]]>
            </summary>
            <updated>2025-12-08T13:43:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1153</id>
            <title type="text"><![CDATA[Apache Kafka]]></title>
            <link rel="alternate" href="https://kafka.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1153"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

Related contents:

- [Why Was Apache Kafka Created? @ Big Data Stream](https://bigdata.2minutestreaming.com/p/why-was-apache-kafka-created).

- [Apache Kafka @ GitHub](https://github.com/apache/kafka).

Related contents:

- [The New Look and Feel of Apache Kafka 4.0 @ The New Stack](https://thenewstack.io/the-new-look-and-feel-of-apache-kafka-4-0/).
- [Kafka: The End of the Beginning @ Materialized View](https://materializedview.io/p/kafka-end-of-beginning).
- [Optimizing Kafka Tracing with OpenTelemetry: Boost Visibility &amp;amp; Performance @ New Relic](https://newrelic.com/blog/how-to-relic/optimizing-kafka-tracing-with-opentelemetry-boost-visibility-performance).
- [Introducing Apache Kafka® 4.1.0: What’s New and How to Upgrade @ Confluent](https://www.confluent.io/blog/introducing-apache-kafka-4-1/).
- [Testing Kafka-based Asynchronous Workflows Using OpenTelemetry @ Signadot](https://www.signadot.com/blog/testing-kafka-based-asynchronous-workflows-using-opentelemetry).
- [Kafka is fast -- I&amp;#039;ll use Postgres @ TopicPartition](https://topicpartition.io/blog/postgres-pubsub-queue-benchmarks).
- [The KFC Architecture Blueprint: Kafka, Flink, and ClickHouse @ Big Data Boutique](https://bigdataboutique.com/blog/kfc-architecture-blueprint-kafka-flink-and-clickhouse).
- [Episode #147 - RabbitMQ, Kafka et les messages brokers @ Code Garage :fr:](https://code-garage.com/podcast/classic/episode-147).]]>
            </summary>
            <updated>2026-03-19T07:15:38+00:00</updated>
        </entry>
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