Showing 3 open source projects for "mac on windows"

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    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

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    Stop vibe-debugging.

    Plug Claude into your app's actual errors.

    AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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  • 1
    Akka

    Akka

    Build concurrent, distributed, and resilient message-driven apps

    Build powerful reactive, concurrent, and distributed applications more easily. Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to...
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  • 2
    SnappyData

    SnappyData

    Memory optimized analytics database, based on Apache Spark

    SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for a unified analytics workload. By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. One common use case for SnappyData is to provide analytics at interactive speeds over...
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  • 3
    Cosmos DB Spark

    Cosmos DB Spark

    Apache Spark Connector for Azure Cosmos DB

    Azure Cosmos DB Spark is the official connector for Azure CosmosDB and Apache Spark. The connector allows you to easily read to and write from Azure Cosmos DB via Apache Spark DataFrames in Python and Scala. It also allows you to easily create a lambda architecture for batch-processing, stream-processing, and a serving layer while being globally replicated and minimizing the latency involved in working with big data.
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