Search Results for "real time software"
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Showing 12 open source projects for "real time software"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Pathway
Python ETL framework for stream processing, real-time analytics, LLM
...Unlike traditional batch processing frameworks, Pathway continuously updates the results of your data logic as new events arrive, functioning more like a database that reacts in real-time. It supports Python, integrates with modern data tools, and offers a deterministic dataflow model to ensure reproducibility and correctness. -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
Fully open source, cloud-native, scalable, micro streaming, and complex event processing system capable of building event-driven applications for use cases such as real-time analytics, data integration, notification management, and adaptive decision-making. Event processing logic can be written using Streaming SQL queries via graphical and source editors, to capture events from diverse data sources, process and analyze them, integrate with multiple services and data stores, and publish output to various endpoints in real time. ... -
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Numaflow
Kubernetes-native platform to run massively parallel data/streaming
Numaflow is a Kubernetes-native tool for running massively parallel stream processing. A Numaflow Pipeline is implemented as a Kubernetes custom resource and consists of one or more source, data processing, and sink vertices. Numaflow installs in a few minutes and is easier and cheaper to use for simple data processing applications than a full-featured stream processing platform. -
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Watermill
Building event-driven applications the easy way in Go
Go library for building event-driven applications. Our goal was to create a tool that is easy to understand, even by junior developers. It doesn't matter if you want to do Event-driven architecture, CQRS, Event Sourcing or just stream MySQL Binlog to Kafka. Watermill was designed to process hundreds of thousands of messages per second. Every component is built in a way that allows you to configure it for your needs. You can also implement your own middleware for the router. Watermill is... -
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HStreamDB
HStreamDB is an open-source, cloud-native streaming database
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications. By subscribing to streams in HStreamDB, any update of the data stream will be pushed to your apps in real-time, and this promotes your apps to be more responsive. You can also replace message brokers with HStreamDB and everything you do with message brokers can be done better with HStreamDB. HStreamDB provides built-in support for event time-based stream processing. ... -
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Padasip
Python Adaptive Signal Processing
Padasip (Python Adaptive Signal Processing) is a Python library tailored for adaptive filtering and online learning applications, particularly in signal processing and time series forecasting. It includes a variety of adaptive filter algorithms such as LMS, RLS, and their variants, offering real-time adaptation to changing environments. The library is lightweight, well-documented, and ideal for research, prototyping, or teaching purposes. Padasip supports both supervised and unsupervised filtering modes and is built to be modular and extensible, making it easy to integrate into larger machine learning pipelines or control systems. -
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Amadeus
Harmonious distributed data analysis in Rust
Amadeus is a high-performance, distributed data processing framework written in Rust, designed to offer an ergonomic and safe alternative to tools like Apache Spark. It provides both streaming and batch capabilities, allowing users to work with real-time and historical data at scale. Thanks to Rust’s memory safety and zero-cost abstractions, Amadeus delivers performance gains while reducing the complexity and bugs common in large-scale data pipelines. It emphasizes developer productivity through a fluent, expressive API and makes it easier to build composable and reliable data transformation pipelines without sacrificing speed or safety. -
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FLOGO
Simplify building efficient & modern serverless functions and apps
Project Flogo is an ultra-light, Go-based open source ecosystem for building event-driven apps. Event-driven, you say? Yup, the notion of triggers and actions are leveraged to process incoming events. An action, a common interface, exposes key capabilities such as application integration, stream processing, etc. All capabilities within the Flogo Ecosystem have a few things in common, they all process events (in a manner suitable for the specific purpose) and they all implement the action... -
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ksqlDB
The database purpose-built for stream processing applications
Build applications that respond immediately to events. Craft materialized views over streams. Receive real-time push updates, or pull current state on demand. Seamlessly leverage your existing Apache Kafka® infrastructure to deploy stream-processing workloads and bring powerful new capabilities to your applications. Use a familiar, lightweight syntax to pack a powerful punch. Capture, process, and serve queries using only SQL. No other languages or services are required. ksqlDB enables you to build event streaming applications leveraging your familiarity with relational databases. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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DSPatch
The Refreshingly Simple C++ Dataflow Framework
Webite: http://flowbasedprogramming.com DSPatch, pronounced "dispatch", is a powerful C++ dataflow framework. DSPatch is not limited to any particular domain or data type, from reactive programming to stream processing, DSPatch's generic, object-oriented API allows you to create virtually any dataflow system imaginable. *See also:* DSPatcher ( https://github.com/MarcusTomlinson/DSPatcher ): A cross-platform graphical tool for building DSPatch circuits. DSPatchables (... -
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Wally
Distributed Stream Processing
Wally is a fast-stream-processing framework. Wally makes it easy to react to data in real-time. By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. -
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ActiveInsight provides real-time detection and reaction to events and patterns. It is a platform that enables the detection of meaningful events within multiple, high frequency, event streams.
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