Skill 디렉토리

AI Agent를 위한 재사용 가능한 Skill을 찾으세요.

작업으로 실제 GitHub Skill을 검색하고 사용 전에 Stars, 신뢰, 감사, 카테고리, 설치 경로를 확인하세요.

모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.

검색 결과: lakehouse

영문 디렉토리

The world's fastest open query engine for sub-second analytics both on and off the data lakehouse. With the flexibility to support nearly any scenario, StarRocks provides best-in-class performance for multi-dimensional analytics, real-time analytics, and ad-hoc queries. A Linux Foundation project.

12K
Stars
85/100
신뢰
카테고리: data-analysis감사

Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

6.7K
Stars
86/100
신뢰
카테고리: ml-automation감사

LakeSoul is an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.

3.2K
Stars
83/100
신뢰
카테고리: data-analysis감사

Next-generation decentralized data lakehouse and a multi-party stream processing network

344
Stars
63/100
신뢰
카테고리: web3-analytics감사

Open-source data lakehouse for biology. Query, trace & validate with a lineage-native lakehouse that supports bio-formats, registries & ontologies. 🍊YC S22

271
Stars
70/100
신뢰
카테고리: devops감사

Quick start: pip install jsoniq ⛈️ RumbleDB 2.1.0 "Cedrus Libani" 🌳 for Apache Spark | Run queries on your large-scale, messy datasets (JSON, text, CSV, Parquet, Delta...) | Data Lakehouse with Updates, Scripting, Declarative Machine Learning and more

239
Stars
66/100
신뢰
카테고리: data-analysis감사

GigAPI is a Timeseries lakehouse for real-time data and sub-second queries, powered by DuckDB OLAP + Parquet Query Engine, Compactor w/ Cloud-Native Storage. Drop-in FDAP alternative ⭐

386
Stars
64/100
신뢰
카테고리: data-analysis감사

End-to-end Data Lakehouse project built on Databricks, following the Medallion Architecture (Bronze, Silver, Gold). Covers real-world data engineering and analytics workflows using Spark, PySpark, SQL, Delta Lake, and Unity Catalog. Designed for learning, portfolio building, and job interviews.

344
Stars
66/100
신뢰
카테고리: data-analysis감사

Use SQL to build ELT pipelines on a data lakehouse.

290
Stars
59/100
신뢰
카테고리: data-analysis감사