Best of SQL — April 2024
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KDnuggets·2y
Ultimate Collection of 50 Free Courses for Mastering Data Science
A comprehensive collection of 50 free courses for mastering data science, covering topics such as Python, SQL, Data Analytics, Business Intelligence, Data Engineering, Machine Learning, Deep Learning, Generative AI, and MLOps.
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Javarevisited·2y
Combining Data from Multiple Tables in SQL Without Using JOIN or UNION
Techniques for combining data from multiple tables in SQL without using JOIN or UNION, including leveraging aggregated subqueries, utilizing EXISTS or NOT EXISTS, selective data insertion, and using temporary tables or CTEs.
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Hacker News·2y
nalgeon/sqlime: Online SQLite playground
Sqlime is an online SQLite playground for debugging and sharing SQL snippets. It supports the latest version of SQLite and includes essential extensions. You can connect any local or remote SQLite database, save queries and databases to GitHub, and even get help from the ChatGPT assistant.
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This Dot·2y
Intro to EdgeDB
EdgeDB is a graph-relational database that provides a novel approach to handling common pain points in data modeling. It offers a powerful schema system, support for defining relations/associations, computed properties, and access policies. EdgeQL is the query language used to interact with the database. EdgeDB nudges users to move more application logic into the database layer, providing constraints, global variables, contexts, and authorization support out-of-the-box. EdgeDB offers both a basic client for executing queries and a TypeScript query builder for type-safe queries. The CLI and Admin UI provide additional tools for managing EdgeDB projects and databases.
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Substack·2ySQL vs Python Data Pipelines
The post discusses the decision of when to use Python and when to use SQL in data pipelines. It emphasizes the importance of striking a balance between the two and making good technical decisions. It also highlights the pitfalls to be careful about in both SQL and Python pipelines.
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GoPenAI·2y
Vector Database Part 3
This post discusses the different types of vector databases available, including SQL databases with vector support, NoSQL databases with vector support, dedicated vector databases, and in-memory key-value databases like Redis. It also covers hybrid search, which combines sparse (keyword/lexical) search and dense (vector) search.
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