MirahLabs Engineering Blog
Technical insights, architectural deep-dives, and system designs authored by our product engineers and AI research leads.
Scaling Python Flask Applications with PostgreSQL
Best practices for configuring database pools, write indexes, caching, and utilizing Docker deployment structures for Flask backends.
Building Production RAG Pipelines with LangChain and PostgreSQL pgvector
How to build Retrieval-Augmented Generation (RAG) systems that ground LLM responses in private documents using LangChain orchestration and PostgreSQL's pgvector extension.
SQLAlchemy 2.0: The Complete Migration Guide
SQLAlchemy 2.0 introduces a new style API, async-first design, and significant performance improvements. Learn what changed and how to migrate your Flask applications.
Vector Databases Compared: Pinecone vs Weaviate vs pgvector
A detailed comparison of three leading vector database solutions—Pinecone, Weaviate, and pgvector—covering performance, scalability, cost, and best-fit use cases.
PostgreSQL Full-Text Search: FTS vs pgvector vs Elasticsearch
Full-text search can be implemented several ways in a PostgreSQL-based stack. Compare native FTS, vector semantic search with pgvector, and Elasticsearch for your search requirements.
Automated Database Migrations in CI/CD Pipelines
Running schema migrations reliably in automated pipelines requires careful ordering and rollback strategies. This guide covers Alembic, Flyway, and migration safety patterns.