VectorETL

Overview

VectorETL is an open-source tool for building end-to-end data and ETL pipelines specifically designed for vector databases and generative AI applications.

Key Features

Data Ingestion:

• Support for multiple data sources
• File formats (PDF, DOCX, TXT, HTML)
• Databases and APIs
• Cloud storage

Transformation:

• Text chunking
• Embedding generation
• Metadata extraction
• Data cleaning

Loading:

• Multiple vector database targets
• Batch and streaming modes
• Error handling and retry logic

Supported Vector Databases

• Milvus
• Qdrant
• Weaviate
• Pinecone
• And more

Use Cases

• Migrating data to vector databases
• Building RAG data pipelines
• Continuous data ingestion
• Data synchronization

Benefits

• Simplified pipeline development
• Pre-built connectors
• Scalable processing
• Error resilience

Availability

Open-source: github.com/ContextData/VectorETL