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  "name": "Apache Spark Streaming",
  "description": "Apache Spark Streaming is an extension of the core Apache Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. It allows data to be ingested from many sources like Kafka, Flume, and Kinesis, and processed using complex algorithms expressed with high-level functions like map, reduce, join, and window.",
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  "archetype": "Challenger",
  "category": "Data Infrastructure",
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  "competitors": [
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      "slug": "amazon-kinesis-data-analytics",
      "name": "Amazon Kinesis Data Analytics"
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    {
      "slug": "apache-flink",
      "name": "Apache Flink"
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  "inboundCompetitors": [
    {
      "slug": "apache-kafka-streams",
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  "parentBrand": null,
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  "updatedAt": "2026-04-11T15:35:29.527+00:00",
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    "founded": "2013",
    "headquarters": "Forest Hill, MD (Apache Software Foundation)",
    "pricing_model": "Free (Open Source / Apache License 2.0)",
    "core_products": "DStream API, Structured Streaming engine, Kafka/Kinesis connectors.",
    "key_differentiator": "Seamless unification of batch and stream processing within a single engine and programming model.",
    "target_markets": "Data Engineers, Data Scientists, Enterprises with Big Data requirements, Fintech, AdTech.",
    "employee_count": "N/A (Open Source Project)",
    "funding_stage": "N/A (Apache Project)",
    "subcategory": "Stream Processing Engine"
  },
  "timestamp": 1775988346587
}