Databases resources for developers

A 10-stage path to a .NET developer job: modern C# on .NET 10, LINQ and async, ASP.NET Core, EF Core and SQL Server, Identity and JWT security, a Web API, Angular, React or Blazor front end, xUnit and integration testing, production features, and Docker, GitHub Actions and Azure. It suits students and developers aiming at banks, telecoms and enterprise software houses. By the end you can build, test, secure and ship one production-ready ASP.NET Core application and explain every choice in it.

• Web
• Backend
• Programming
• Databases

A short, nine-stage path for picking the right database for each job in an app: describe your data first, then relational, document, key-value and cache, search, vector, columnar and warehouse, graph, time-series and object storage, each with a hands-on task, and finally managed versus self-hosted, cloud equivalents, free tiers and cost. It suits students and developers starting a project. By the end you can write a database decision for your own app and defend every choice in it.

• Web
• Databases
• Backend
• Cloud

A seven-stage plan for building and running a complete web product on your own, in Next.js, MERN, Django with React, or Spring Boot with React: web foundations, Git and React, the server side, data modelling in PostgreSQL or MongoDB, APIs with authentication and caching, deployment to Linux or AWS with CI/CD, and one shipped product with real users. It suits developers who want to own a product end to end. By the end you can model data, build a secure API and UI, deploy it and ship every change through a pipeline.

• Web
• Frontend
• Backend
• Databases

The official searchable database of DAAD scholarships and selected other funding for study and research in Germany, filterable by your country, level and subject. It includes programmes such as EPOS for graduates from developing countries with work experience.

• Career
• Databases
• Higher studies

A free, project-based course that takes you through a whole modern data stack: Docker, Terraform, orchestration, BigQuery, dbt, Spark and Kafka, ending in a pipeline you design yourself. The best free end-to-end introduction to the job, as long as you do the homework and the final project rather than only watching.

• Programming
• Databases
• DevOps
• Cloud

A free online book that explains SQL indexing for developers, from how a B-tree is laid out to why a particular WHERE clause can or cannot use an index. It covers Oracle, MySQL, PostgreSQL, SQL Server and Db2 with product-specific notes. It is the clearest resource for turning index theory into faster queries.

• Web
• Databases
• Backend

A quick-revision companion to the Data analytics roadmap: what analysts do, spreadsheets, SQL for analysis, statistics, cleaning and modelling, charts, dashboards and storytelling, and the first analyst role, plus a chapter for your tool. Power BI, Tableau and Python editions each have eight chapters with formulas, SQL, DAX, Tableau calculations or pandas snippets. Use it after each stage, while building a dashboard, and before an analyst technical round or take-home task.

• Databases
• Programming

A quick-revision companion to the Sefism backend roadmap: an essentials chapter for your stack, then terminal and Git, how HTTP works, relational databases and SQL, API design, authentication and API security, caching and queues, testing and CI/CD, and architecture and reliability. It comes in seven editions (Node.js, Python, Java, C#, Go, PHP and Rust), each concept with a short example and the mistake to avoid. Read a chapter before a project, an exam or a technical conversation.

• Web
• Backend
• Databases
• DevOps

The companion to the SQL and databases roadmap in PostgreSQL, MySQL and SQL Server editions: setup, single-table queries, joins, aggregation and window functions, schema design, changing data safely, indexes and query plans, SQL in applications, and a short MongoDB comparison. Each concept is a line or two with your dialect syntax and the classic mistake to avoid.

• Web
• Databases
• Backend

An eight-stage path to a data or BI analyst role, with Excel and Power BI, Tableau or Python as your main tool: how analysts think, spreadsheets properly, SQL for analysis, the statistics you need, your tool in depth, cleaning and modelling data, charts, dashboards and storytelling, and a portfolio for your first role. It suits students and early-career engineers from any background. By the end you can take a vague business question, answer it with trustworthy numbers, and present a clear recommendation backed by two or three portfolio projects.

• Databases
• Programming
• Career

Harvard's free CS50 course on databases, taught by Carter Zenke and David J. Malan. Seven lectures move from querying to relating, designing, writing, viewing, optimising and scaling databases, starting with SQLite and ending with PostgreSQL and MySQL, with problem sets and a final project. It suits beginners and working developers who can write basic SELECT queries but do not yet know how to design a schema or make queries fast.

• Web
• Databases
• Backend

A seven-stage plan for building the server side of real products in Node.js, Python, Java, C#, Go, PHP or Rust: your language and HTTP, PostgreSQL and SQL, API design, authentication and API security, caching and queues, testing with CI/CD and Docker, and architecture and reliability. It suits people who can already write a little code and want a backend role. By the end you can design a schema and an API, secure it, make it fast, test and ship it in containers, and explain the choices behind it.

• Web
• Backend
• Databases
• DevOps

A quick-revision companion to the Sefism full stack roadmap in seven chapters: web foundations, Git, npm and React, the server side, data modelling, APIs with authentication and caching, deployment with CI/CD, Linux and AWS, and shipping a complete product. It comes in Next.js, MERN, Django and React, and Spring Boot and React editions, so the server and database chapters match your stack. Skim a chapter before a project or a technical conversation, and use it as a checklist before you ship.

• Web
• Frontend
• Backend
• Databases

A beginner friendly, text based course on relational database design: data modelling, entity relationship diagrams, keys and integrity constraints, functional dependencies and normalisation up to BCNF and beyond. It finishes with nine case studies, from hospital and bank systems to an Instagram style app, e-commerce and ticket booking. For developers and students who want to design schemas that stay pleasant to work with years later.

• Web
• Databases
• System design
• Backend

A text-based course on how databases work underneath: storage and page layout, indexing, transactions and ACID, concurrency control, partitioning and sharding, replication and consistency, consensus and leader election, recovery, and the main NoSQL families. It ends with case studies designing the databases behind Quora, TikTok, Airbnb and Snapchat. It suits engineers who want their database choices in system design answers to be defensible rather than hand-waved.

• System design
• Databases
• Backend
• Job search

A SQL course for interviews that reviews the basics, order of execution, functions, subqueries, joins, set operations, DDL and DML, then works through 69 interview problems graded easy to hard plus 14 unguided test problems, run against a live database in the browser. It suits backend, data and analytics candidates whose SQL stops at a simple inner join, or who need a fast refresher before a SQL round.

• Job search
• Databases
• Backend

A practical guide to PostgreSQL best practices for application developers. It covers schema design and data types, constraints, indexing with EXPLAIN, query patterns that avoid N+1 problems, migrations that do not lock production, connection pooling, transactions and isolation, backups you have actually restored, and roles with least privilege.

• Web
• Databases
• Backend

A practical guide to MongoDB best practices for application developers. It covers supported versions, schema design around access patterns, schema validation including the new constraint level in 9.0, compound indexes with the ESR guideline, queries and aggregation within memory limits, write concern and transactions, driver connection handling, and the security checklist for a production deployment.

• Web
• Databases
• Backend

A pre-release checklist for schema and data migrations on a live database. It covers backward-compatible expand and contract steps, how each kind of change locks a table in PostgreSQL and MySQL, building indexes online, batching backfills, rehearsing on production-sized data, backups and rollback, deploy ordering with application code and what to watch while it runs, with notes for MongoDB.

• Databases
• Backend
• DevOps

Best practices for batch data pipelines, checked against the Apache Airflow and dbt documentation and Google's guidance on data validation for ML systems. It covers idempotent, re-runnable tasks, orchestrator hygiene, layered transformations, data tests and freshness checks, ownership and lineage, and monitoring for silent failures.

• Data
• Databases

Best practices for modeling analytics data, checked against the Kimball Group's dimensional modeling techniques, Microsoft's dimensional modeling guidance and the dbt documentation. It covers the grain, fact and dimension tables, slowly changing dimensions, dbt marts and naming, tests and contracts, and defining metrics once in a semantic layer.

• Data
• Databases

Best practices for answering questions with data in SQL, pandas and Polars, checked against Google's Good Data Analysis guide and the pandas, Polars and PostgreSQL documentation. It covers framing the question, reading data correctly, joins and grain, aggregation pitfalls, reproducible notebooks, checking results and communicating findings.

• Data
• Databases

A reference in 10 chapters and 78 concepts for picking the right database for each job: a decision chart from data and access patterns to a database type, then relational, document, key-value and cache, search, vector, columnar and warehouse, graph, time series and object storage, with one at-a-glance card per type and tables of matching managed services on AWS, Azure and Google Cloud. It follows the Sefism Choosing the right database roadmap. Use it whenever you start a project or someone suggests adding a database.

• Web
• Databases
• Backend
• Cloud

The official documentation for Elasticsearch, the search and analytics engine behind many product search bars, log tools and site search. Learn how documents become an inverted index, how full-text queries are scored, and how to run it locally or on Elastic Cloud.

• Web
• Databases
• Backend