{"repo":"khive-ai/pydapter","free":true,"listed":false,"github":"https://github.com/khive-ai/pydapter","clone":"git clone https://github.com/khive-ai/pydapter.git","description":"adapt data to and from every format","language":"Python","stars":28,"topics":["ai","data","database","pydantic","schema","vector"],"license":"Apache-2.0","category":"databases-storage","readme_excerpt":"🔄 Pydapter: Infrastructure for the Post-Database World --- The Problem We're Solving Modern applications don't fit in one database anymore. Your LLM extracts insights that need PostgreSQL for transactions, Qdrant for vector search, Neo4j for relationships. Each integration means different APIs, different patterns, weeks of custom code. We calculated it: engineers spend 40% of their time on data plumbing instead of building intelligence. Why Pydapter Exists We believe the data layer should be invisible. When you build an application, you should think about your domain models and business logic, not about cursor management or connection pooling. Pydapter makes storage a deployment decision, not an architecture decision. --- The Paradigm Shift Traditional thinking: Choose a database, design around its constraints, live with the tradeoffs forever. The new reality: Data flows where it provides the most value. When integration friction disappears, architecture becomes liquid. --- What This Enables 1. Multi-Modal AI Pipelines Your LLM processes a document and extracts entities. Those entities need to be stored for compliance (PostgreSQL), searchable by meaning (vector database), and analyzed for relationships (graph database). With Pydapter, it's the same three lines of code for each destination. 2. Storage-Agnostic Applications Deploy the same application on-premise with PostgreSQL, in AWS with DynamoDB, or at the edge with SQLite. Just change configuration, not code. 3. Evolution","default_branch":null,"files":null,"tree":[],"storefront":"/r/khive-ai","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/khive-ai/pydapter/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}