Showing 8 open source projects for "stream windows"

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  • 1
    Alpakka Kafka

    Alpakka Kafka

    Alpakka is a Reactive Enterprise Integration library for Java

    The Alpakka project is an open source initiative to implement stream-aware and reactive integration pipelines for Java and Scala. It is built on top of Akka Streams and has been designed from the ground up to understand streaming natively and provide a DSL for reactive and stream-oriented programming, with built-in support for backpressure. Akka Streams is a Reactive Stream and JDK 9+ java.util.concurrent.Flow-compliant implementation and therefore fully interoperable with other...
    Downloads: 0 This Week
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  • 2
    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...
    Downloads: 6 This Week
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  • 3
    FS2

    FS2

    Compositional, streaming I/O library for Scala

    FS2 (“Functional Streams for Scala”) is a purely functional, effectful abstraction for stream processing on the JVM. Built on Cats Effect, it enables compositional resource-safe streaming workflows with robust error handling, back-pressure, pull/push semantics, and support for concurrent and interruptible pipelines.
    Downloads: 1 This Week
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  • 4
    Akka HTTP

    Akka HTTP

    The Streaming-first HTTP server/module of Akka

    The Akka HTTP modules implement a full server- and client-side HTTP stack on top of akka-actor and akka-stream. It’s not a web framework but rather a more general toolkit for providing and consuming HTTP-based services. While interaction with a browser is of course also in scope it is not the primary focus of Akka HTTP. Akka HTTP follows a rather open design and many times offers several different API levels for “doing the same thing”. You get to pick the API level of abstraction that is...
    Downloads: 2 This Week
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  • 5
    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...
    Downloads: 0 This Week
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  • 6
    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.
    Downloads: 0 This Week
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  • 7
    Graphcool Framework

    Graphcool Framework

    Graphcool is an open-source backend development framework

    Graphcool was an open-source framework for developing and deploying GraphQL-based backends. It acts as a “backend-as-a-service / framework” that lets you define your data model via GraphQL SDL (Schema Definition Language), and in turn generates a GraphQL CRUD API, supports nested mutations, filtering, pagination, and real-time subscriptions. Graphcool separates the business logic from stateful storage components, allowing the stateful parts (database, subscription engine) to scale...
    Downloads: 0 This Week
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  • 8
    Summingbird

    Summingbird

    Streaming MapReduce with Scalding and Storm

    Summingbird is a streaming + batch hybrid computation framework developed by Twitter. Its aim is to let developers express data aggregation pipelines in a unified way, where the same logic can run either in real time (stream) or in batch mode, and the results can be merged or reconciled. In effect, Summingbird abstracts over multiple execution engines (such as Storm, Scalding, etc.) to provide one high-level program that composes transformations and aggregations, and then executes them in...
    Downloads: 0 This Week
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