Search Results for "event processing"
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Showing 57 open source projects for "event processing"
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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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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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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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Apache Flink
Stream processing framework with powerful stream
Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level APIs—DataStream and Table/SQL—to express transformations, joins, and stateful patterns, while specialized libraries support CEP, machine learning workflows, and connectors. ... -
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Commanded
Use Commanded to build Elixir CQRS/ES applications
Commanded is an Elixir framework for implementing CQRS (Command Query Responsibility Segregation) and Event Sourcing patterns. It provides domain-driven design tools—aggregates, commands, events, and projections—backed by an event store (e.g. PostgreSQL). -
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Kapacitor
Open source framework for processing, monitoring, and alerting
Open source framework for processing, monitoring, and alerting on time series data. Kapacitor is a real-time data processing engine for monitoring and alerting, specifically designed to work with time-series data from InfluxDB. -
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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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Tokio
A runtime for writing reliable asynchronous applications with Rust
Build reliable network applications without compromising speed, with Tokio! Tokio is an event-driven, non-blocking I/O platform and asynchronous runtime for the Rust programming language that allows you to write reliable and slim network applications. At a high level, Tokio provides a number of components needed for building asynchronous applications. These include a multithreaded, work-stealing based task scheduler; a reactor that's supported by the operating system's event queue; and asynchronous TCP and UDP sockets. ... -
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Broadway
Concurrent and multi-stage data ingestion and data processing
...Developers can enrich pipelines with batching, concurrency control, and metrics reporting, simplifying the management of complex data ingestion and processing systems. Broadway is often used for event processing, stream handling, and background jobs, offering both performance and clarity in Elixir’s functional style. -
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Benthos
Fancy stream processing made operationally mundane
Benthos is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads. It comes with a powerful mapping language, is easy to deploy and monitor, and ready to drop into your pipeline either as a static binary, docker image, or serverless function, making it cloud native as heck. Delivery guarantees can be a dodgy subject. Benthos processes and... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Apache Spark
A unified analytics engine for large-scale data processing
...With Spark Streaming (microbatches) and Structured Streaming, it delivers low-latency event processing suitable for real-time analytics. The built-in MLlib library provides scalable machine learning algorithms, while GraphX enables graph computations integrated with data pipelines. Spark supports multiple languages—Scala, Java, Python, R—and connects with many storage systems like HDFS, S3, Cassandra, and streaming platforms like Kafka, making it a versatile choice for big data workloads in analytics, ETL, and data science. -
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Akka
Build concurrent, distributed, and resilient message-driven apps
...Small memory footprint; ~2.5 million actors per GB of heap. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. -
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Asynq
Simple, reliable, and efficient distributed task queue in Go
Asynq is a Go library for queueing tasks and processing them asynchronously with workers. It's backed by Redis and is designed to be scalable yet easy to get started. Client puts tasks on a queue. Server pulls tasks off queues and starts a worker goroutine for each task. Tasks are processed concurrently by multiple workers. Task queues are used as a mechanism to distribute work across multiple machines. A system can consist of multiple worker servers and brokers, giving way to high... -
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Laravel Webhook Client
Receive webhooks in Laravel apps
A webhook is a way for an app to provide information to another app about a specific event. The way the two apps communicate is with a simple HTTP request. This package allows you to receive webhooks in a Laravel app. It has support for verifying signed calls, storing payloads and processing the payloads in a queued job. -
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Zappa - Serverless Python
Serverless Python
Zappa makes it super easy to build and deploy server-less, event-driven Python applications (including, but not limited to, WSGI web apps) on AWS Lambda + API Gateway. Think of it as "serverless" web hosting for your Python apps. That means infinite scaling, zero downtime, zero maintenance - and at a fraction of the cost of your current deployments! With a traditional HTTP server, the server is online 24/7, processing requests one by one as they come in. -
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Task Scheduler
Cooperative multitasking for Arduino, ESPx, STM32, nRF and more
Cooperative multitasking for Arduino, ESPx, STM32 and other microcontrollers. A lightweight implementation of cooperative multitasking (task scheduling). An easier alternative to preemptive programming and frameworks like FreeRTOS. You mostly do not need to worry about pitfalls of concurrent processing (races, deadlocks, livelocks, resource sharing, etc.). The fact of cooperative processing takes care of such issues by design. -
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Nuclio
High-Performance Serverless event and data processing platform
Nuclio is an open source and managed serverless platform used to minimize development and maintenance overhead and automate the deployment of data-science-based applications. Real-time performance running up to 400,000 function invocations per second. Portable across low laptops, edge, on-prem and multi-cloud deployments. The first serverless platform supporting GPUs for optimized utilization and sharing. Automated deployment to production in a few clicks from Jupyter notebook. Deploy one of... -
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EasyExcel
Lightweight Java library developed by Alibaba for reading and writing
EasyExcel is a Java library focused on reading and writing Excel files with very low memory usage, making it suitable for large datasets that overwhelm traditional APIs. It uses streaming/event-driven parsing to avoid loading entire workbooks into memory, and it maps rows to Java objects via simple annotations. Writers support multiple sheets, custom styles, merged cells, and template-based filling so production reports remain maintainable. The API emphasizes developer ergonomics: callbacks... -
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G4P
GUI controls for Processing
This project is about developing a set of 2D GUI controls for the Processing language. V4.2 is compatible with Processing 3 V3.5.4 is the last version compatible with Processing 2. -
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KubeEdge
Kubernetes Native Edge Computing Framework (project under CNCF)
...It also supports MQTT which enables edge devices to access through edge nodes. With KubeEdge it is easy to get and deploy existing complicated machine learning, image recognition, event processing, and other high-level applications to the Edge. With business logic running at the Edge, much larger volumes of data can be secured & processed locally where the data is produced. With data processed at the Edge, the responsiveness is increased dramatically and data privacy is protected. -
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An innovative Open Source CEP (Complex Event Processing) engine. It implements the event stream processing as a library embeddable in C++ and Perl. You can think of the Complex Event Processing engine as an in-memory database driven by triggers, or a data-flow machine, or a spreadsheet on steroids (and without the GUI part).
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DAE Tools Project
Object-oriented equation-based modelling and optimisation software
...It is not a modelling language nor a collection of numerical libraries but rather a higher level structure – an architectural design of interdependent software components providing an API for: - Model development/specification - Activities on developed models, such as simulation, optimisation, sensitivity analysis and parameter estimation - Processing of the results, such as plotting and exporting to various file formats - Report generation - Code generation, co-simulation and model exchange The following class of problems can be solved by DAE Tools: - Initial value problems of implicit form - Index-1 DAE systems - With lumped or distributed parameters - Steady-state or dynamic - Continuous with some elements of event-driven systems -
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Kisekae UltraKiss
Kisekae UltraKiss is a full featured integrated development environmen
UltraKiss is a computer program that implements the Kisekae Set system, KiSS, a Japanese graphics system originally developed to facilitate costume changes on virtual dolls. UltraKiss was developed to help artists build their KiSS sets. It is a full featured viewer for all KiSS dolls, games, and visual applications. It is also a complete graphical development environment for creating KiSS applications. It fully implements the FKiSS event driven programming language up to and including... -
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Livewire Best Practices
Laravel Livewire Best Practices
This repository is a curated list of general recommendations on how to use Laravel Livewire framework to meet enterprise concerns regarding the security, performance, and maintenance of Livewire components. Avoid passing objects to the component's public properties if possible. Use primitive types: strings, integers, arrays, etc. That's because Livewire serializes/deserializes your component's payload with each request to the server to share the state between the frontend & backend. If you... -
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go-coffeeshop
A practical event-driven microservices demo
go-coffeeshop is a sample application that demonstrates how to build scalable and maintainable systems using Go, following clean architecture principles and domain-driven design concepts. It simulates a coffee shop system, providing a realistic context for implementing business logic, APIs, and data handling. The project is structured to separate concerns clearly, with layers for domain logic, application services, infrastructure, and interfaces. It showcases best practices for building... -
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Brigade
Event-driven scripting for Kubernetes
Brigade is a full-featured, event-driven scripting platform built on top of Kubernetes. It integrates with many different event sources, more are always being added, and it's easy to create your own if you need something specific. The best part is that Kubernetes is well-abstracted so even team members without extensive Kubernetes experience or without direct access to a cluster can be productive.
