Data Engineering · Bibliothek

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...

Quelle

GitHub

Sprache

Java

Domänen

Data Engineering

With dbt, data analysts and engineers can build analytics the way engineers build applications.

Quelle

PyPI

Domänen

Data Engineering

High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.

Quelle

GitHub

Sprache

Python

Domänen

Data Engineering

Einsatzzwecke

Retrieval-Augmented Generation (RAG), Workflows

Programmatically author, schedule and monitor data pipelines

Quelle

PyPI

Domänen

Data Engineering

Einsatzzwecke

Workflows

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

Quelle

GitHub

Sprache

Python

Domänen

Data Engineering, Rust

Blazingly fast DataFrame library

Quelle

PyPI

Domänen

Data Engineering

LakeSoul is an end-to-end, realtime cloud-native Lakehouse framework for fast data ingestion, concurrent updates, incremental analytics, multimodal data processing and vector search — powering next-generation BI and AI workloads.

Quelle

GitHub

Sprache

Rust

Domänen

Data Engineering

Einsatzzwecke

Retrieval-Augmented Generation (RAG)