8 repository-uri
Systems for managing the movement and transformation of data between user interfaces and backend services.
Distinguishing note: Focuses on the flow of data between layers rather than storage management.
Explore 8 awesome GitHub repositories matching data & databases · Data Flow Orchestrators. Refine with filters or upvote what's useful.
Appsmith is a low-code platform designed for building internal business tools, such as operational dashboards and administrative panels. It enables developers to construct dynamic user interfaces by dragging and dropping modular widgets onto a canvas and binding them directly to backend data sources. The platform utilizes a reactive framework that automatically updates interface elements and triggers functions whenever underlying data or widget properties change, eliminating the need for manual event handling. The platform distinguishes itself through a server-side proxy architecture that exe
Enables execution of queries and custom logic to retrieve, update, or submit information between user views and backend services.
Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag
Wraps audio, text, and images into frames that flow through a modular pipeline of processors.
This project is a reference implementation of the Model-View-ViewModel pattern using Android Jetpack components. It serves as an architecture template and layering guide, dividing application code into view, domain, and data layers to ensure a unidirectional flow of dependencies. The implementation focuses on state management and configuration change handling. It demonstrates how to synchronize UI updates across multiple screens using shared state containers and preserves application state during transitions between portrait and landscape orientations. The codebase covers a broad surface of
Manages the movement of data between layers to ensure a single source of truth.
Apache Camel este un framework de integrare enterprise și un motor de integrare Java conceput pentru a ruta și media datele între sisteme disparate. Acesta funcționează ca un middleware multi-runtime care implementează tipare de integrare enterprise standardizate pentru a gestiona modul în care mesajele sunt rutate, transformate și procesate. Framework-ul include un gateway specializat pentru a conecta modelele de limbaj mari (LLM) la datele enterprise și sistemele interne folosind protocoale de comunicare dedicate. Utilizează o bibliotecă vastă de conectori pre-construiți pentru a face legătura între diferite protocoale de comunicare și a permite schimbul de date între aplicații software incompatibile. Sistemul suportă orchestrarea fluxului de date printr-un pipeline bazat pe mesaje, permițând utilizatorilor să definească logica de rutare prin Java, XML, YAML sau un designer vizual de fluxuri de lucru. Aceste procese de integrare pot fi implementate ca un serviciu standalone sau încorporate în framework-uri gazdă precum Spring Boot și Quarkus.
Defines and executes rules to orchestrate the movement and transformation of information between APIs, brokers, and cloud services.
GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without
Limits the time range of source data read by the continuous aggregation flow engine.
Effector is a reactive state management library and data flow orchestrator designed for building complex, event-driven applications. It models application logic as a directed acyclic graph, where state updates and asynchronous side effects propagate automatically through declarative pipelines. By decoupling business logic from user interface layers, it allows developers to maintain state in independent containers that communicate via standard interfaces, ensuring the system remains framework-agnostic. The library distinguishes itself through its robust support for isolated execution scopes, w
Connects events, stores, and effects using declarative operators to transform, filter, and route data updates through application logic.
Streem este un limbaj de programare bazat pe fluxuri (stream-based) și un orchestrator de pipeline-uri de date. Oferă un limbaj specific domeniului (DSL) pentru definirea fluxurilor de date concurente, permițând utilizatorilor să lege sursele de date la destinații printr-o secvență de operațiuni care transformă și filtrează elementele individuale ale fluxului. Sistemul utilizează o sintaxă de script personalizată pentru a defini conexiunile fluxului de date și definițiile pipeline-ului. Acest lucru permite orchestrarea procesării concurente a datelor, unde mai multe etape ale pipeline-ului se execută simultan pentru a muta elementele de date prin sistem. Platforma acoperă transformarea funcțională a datelor și compoziția bazată pe etape, aplicând funcții specifice pentru a modifica sau filtra elementele pe măsură ce trec printr-un lanț secvențial de operațiuni legate.
Manages the movement of information from a source to a destination through a series of linked operations.
docetl is an AI-powered document ETL tool and map-reduce orchestrator designed to transform large collections of unstructured documents into structured, queryable tables using language models. It provides a declarative pipeline framework for extracting, cleaning, and transforming data from sources such as PDFs and text files into predefined schemas. The project distinguishes itself through a semantic data integration suite that enables joining datasets and resolving duplicate entities based on embedding-based similarity. It includes an interactive prompt playground for developing and optimizi
Provides tools for chunking documents and sampling subsets to accelerate data extraction iteration.