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Anton GoncharovAI systems developer
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Computer Data-Base Organization

James Martin

  • Databases

A 1970s classic on how databases work inside. Martin separates the logical organization of data — how programs see it — from the physical — how it lies on disk — and covers hierarchical, network and relational structures, indexes, hashing, inverted files and data protection.

Key ideas

  1. The logical schema and physical storage are different levels, and changing one without breaking the other is the main goal of a DBMS.
  2. The access method is chosen by the queries: sequential, indexed or hashed.
  3. An inverted file is the basis for searching by any field, not just by key.
  4. Data outlives programs, so the schema is designed for the whole organization, not for one application.

Where and how I applied it

  • Demo · Web app · RAG · neural network in the browser

    Search sandbox

    BM25 keyword search follows the inverted file principle: from a word to the fragments where it occurs, not a scan of all the text.

  • Demo · Web app · Laravel · PostgreSQL

    Warehouse system on Laravel

    Stock is the sum of postings, and the stock view is rebuilt from the journal: how users see the data is separate from how it is stored.

  • Demo · Web app · question → SQL → chart · PostgreSQL in the browser

    AI data analyst

    The semantic layer separates the manager’s concepts — revenue, average order value, profit — from the six-table schema.

More on the shelf

  • Reading

    Hands-On APIs for AI and Data Science

    Ryan Day

    A practical book on building an API for data and connecting AI to it. The running project is a FastAPI service with a database and documentation, then an SDK for it, using the API in analytics and, finally, LangChain agents that call the API themselves.

    AI and agentsPythonAPIApplied in 3 projects

  • Reading

    Server Applications in Python, Django, Flask and FastAPI

    R. S. Bukharev

    The path of server-side development in Python, from sockets and protocols to architecture and launch on a server. Django, Flask and FastAPI are covered through real projects: a CRM system, a Telegram bot with server-side logic, a REST API for a mobile app and a WebSocket chat. Separate chapters cover caching and scaling, Docker and Kubernetes, PostgreSQL, MySQL, SQLite and MongoDB, and security: password hashing, JWT and OAuth 2.0, protection against SQL injection, XSS and CSRF, TLS.

    ProgrammingPythonBackendApplied in 1 project