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google/tensorstore

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View on GitHub↗
1,522 stele·142 fork-uri·C++·7 vizualizărigoogle.github.io/tensorstore↗

Tensorstore

Library for reading and writing large multi-dimensional arrays.

Features

  • Big Data and Distributed Computing - Reading and writing large multi-dimensional arrays.
  • Stream Processing - Reads and writes large multi-dimensional arrays.

Istoric stele

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Alternative open-source pentru Tensorstore

Proiecte open-source similare, clasificate după numărul de funcționalități comune cu Tensorstore.
  • aklivity/zillaAvatar aklivity

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    🦎 A multi-protocol edge & service proxy. Seamlessly interface web apps, IoT clients, & microservices to Apache Kafka® via declaratively defined, stateless APIs.

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    Vezi pe GitHub↗690
  • apache/beamAvatar apache

    apache/beam

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    Apache Beam is a distributed data pipeline framework and unified data processing model designed to handle both bounded batch data and unbounded real-time streams. It provides a system for building scalable, data-parallel workflows that operate across compute clusters using a single programming model. The framework utilizes a cross-runner pipeline abstraction that decouples the data processing logic from the underlying execution backend, allowing the same pipeline to run on different distributed compute engines. It supports multi-language pipeline development by translating high-level code fro

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  • apache/flinkAvatar apache

    apache/flink

    26,086Vezi pe GitHub↗

    Apache Flink is a distributed processing engine designed for both high-throughput, low-latency data streams and finite batch workloads. It functions as a stateful stream processor and a SQL stream processing engine, providing a unified runtime to execute relational queries and event-based transformations. The system is distinguished by its ability to manage persistent operator state to ensure exactly-once processing guarantees and consistency during failures. It features specialized capabilities for complex event processing to detect temporal patterns and handles out-of-order events using eve

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  • airtai/faststreamAvatar airtai

    airtai/faststream

    5,234Vezi pe GitHub↗

    FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified abstraction layer for interacting with various message brokers, enabling developers to manage event production and consumption through a consistent interface while maintaining access to native provider-specific features. The framework centers on a decorator-based routing model that binds application logic directly to broker topics, supported by a built-in dependency injection container that resolves resources at runtime. The framework distinguishes itself through its deep int

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Vezi toate cele 30 alternative pentru Tensorstore→

Întrebări frecvente

Ce face google/tensorstore?

Library for reading and writing large multi-dimensional arrays.

Care sunt principalele funcționalități ale google/tensorstore?

Principalele funcționalități ale google/tensorstore sunt: Big Data and Distributed Computing, Stream Processing.

Care sunt câteva alternative open-source pentru google/tensorstore?

Alternativele open-source pentru google/tensorstore includ: aklivity/zilla — 🦎 A multi-protocol edge & service proxy. Seamlessly interface web apps, IoT clients, & microservices to Apache Kafka®… apache/beam — Apache Beam is a distributed data pipeline framework and unified data processing model designed to handle both bounded… apache/flink — Apache Flink is a distributed processing engine designed for both high-throughput, low-latency data streams and finite… apache/kafka — Kafka is a distributed event streaming platform designed for capturing, storing, and processing real-time data streams… apache/samza — Mirror of Apache Samza. airtai/faststream — FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified…