Library for reading and writing large multi-dimensional arrays.
Las características principales de google/tensorstore son: Big Data and Distributed Computing, Stream Processing.
Las alternativas de código abierto para google/tensorstore incluyen: 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…
🦎 A multi-protocol edge & service proxy. Seamlessly interface web apps, IoT clients, & microservices to Apache Kafka® via declaratively defined, stateless APIs.
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
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
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