database

DuckLake Is an Integrated Data Lake and Catalog Format.

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DuckLake: An integrated data lake and catalog format from DuckDB, using Parquet and SQL databases for advanced features without complexity. Supports PostgreSQL, SQLite, MySQL, and DuckDB for metadata management. Key features include snapshots, time travel queries, ACID transactions, and performance optimization. DuckLake offers a lightweight solution for collaborative data access and is licensed under MIT. Documentation available for setup and usage.

https://ducklake.select/

Database Relationship Diagrams Design Tool

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dbdiagram.io is a tool for creating ER diagrams using code, aimed at developers and data analysts. It offers features like SQL statement generation, diagram sharing, and integration with SQL databases and web frameworks. The platform is free with a personal plan and enhances documentation and analytics through DBML. Developed by Holistics.io, it supports efficient visualization of database schemas.

https://dbdiagram.io/home

YAGRI: You Are Gonna Read It

YAGRI (You are gonna read it) advises against minimal data storage, suggesting engineers proactively store likely useful metadata (e.g., timestamps, user actions) to aid debugging and analytics. Commonly overlooked fields include created/updated/deleted timestamps and user permissions. While not every field may be useful, having extra data can be invaluable, especially when issues arise. Balancing data storage is crucial; too much logging is unnecessary, but sufficient data tracking enhances project integrity.

https://www.scottantipa.com/yagri

(All) Databases Are Just Files. Postgres Too

All databases, including PostgreSQL, are fundamentally just files, but interaction with PostgreSQL can feel complex due to its structure. Understanding components like data directories, configuration files, and commands enhances usability and workflow efficiency. Simplifying PostgreSQL setup fosters better debugging and control, avoiding detachment typical of default installations. While manual management is suited for development, grasping PostgreSQL's processes helps cultivate confidence and optimization in data handling, similar to the user-friendly experiences offered by SQLite and DuckDB.

https://tselai.com/all-databases-are-just-files

PostgreSQL BM25 Full-Text Search: Speed Up Performance With These Tips

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PostgreSQL Full-Text Search (FTS) can outperform dedicated search engines when optimized correctly. A benchmark showed significant speeds, with optimizations yielding a ~50x performance increase by pre-calculating and storing the tsvector, and configuring GIN indexes properly. Common pitfalls include calculating tsvector on-the-fly and using the default GIN index setting (fastupdate=on), which hinders performance. For advanced ranking tasks, the VectorChord-BM25 extension may be required, offering better relevance scoring than standard methods. Optimal configurations reveal that standard FTS is faster than often perceived.

https://blog.vectorchord.ai/postgresql-full-text-search-fast-when-done-right-debunking-the-slow-myth

Database Protocols Are Underwhelming

Database protocols are outdated and complex, handling mutable state poorly, complicating connection management and error recovery. SQL lacks explicit idempotency, making safe query retries difficult. Introducing features like idempotency keys could enhance retry safety. Prepared statements add overhead and session limitations, suggesting the need for a digest-based system for better resource management. Overall, improving database protocols could significantly enhance developer usability without altering SQL syntax.

https://byroot.github.io/performance/2025/03/21/database-protocols.html

Why DuckDB Is My First Choice for Data Processing

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DuckDB is my preferred data processing tool for its simplicity, speed, and features. It's an open-source SQL engine that runs in-process, optimized for analytics, allowing fast operations like joins and aggregations. DuckDB easily installs via Python with no dependencies, speeds up CI testing, and simplifies SQL writing. Its friendly SQL dialect, support for various file types, and full ACID compliance enhance its usability in data pipelines. Additionally, it has a robust documentation and community support for building high-performance UDFs, making it a strong choice over other engines like Spark or Postgres.

https://www.robinlinacre.com/recommend_duckdb/

Life Altering Postgresql Patterns

Ethan McCue outlines effective PostgreSQL practices for improved database management. Key recommendations include:

  1. Use UUID primary keys for easier sharing and generation.
  2. Include created_at and updated_at for useful record tracking.
  3. Apply on update restrict, on delete restrict to foreign keys to prevent unintentional data loss.
  4. Utilize schemas to organize tables better.
  5. Implement enum tables for flexible value management.
  6. Name tables in singular form to reflect individual row representation.
  7. Use concatenated names for join tables in many-to-many relationships.
  8. Prefer soft deletes with nullable timestamps to avoid permanent data loss.
  9. Track status changes using a log-like structure with a timestamp.
  10. Use a special system_id for critical rows.
  11. Limit use of views due to complexity in management.
  12. Leverage JSON in queries for efficient data retrieval.

These strategies collectively enhance PostgreSQL usability and data integrity.

https://mccue.dev/pages/3-11-25-life-altering-postgresql-patterns

You Can Make Postgres Scale

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Postgres can scale, despite controversy. Challenges include hardware needs and write capacity issues often due to lock contention or idle transactions. A community effort successfully implemented sharding to balance and increase write workloads across multiple databases, aligning with the engineering principle of solving problems fundamentally. The process involved complex steps like synchronizing data and rewriting codes. Ultimately, they created a scalable setup with 36 databases and a tool, PgDog, to automate future scaling. The project aims to demonstrate that Postgres can effectively scale as needed.

https://pgdog.dev/blog/you-can-make-postgres-scale

SpacetimeDB

SpacetimeDB Live: Maincloud offers 90% off limited time. It's an integrated multiplayer app platform replacing traditional servers with direct database connections, enabling fast, efficient game backend development. With low latency and high throughput, it supports user-generated logic and real-time queries. Features include atomic transactions, time-travel state rollback, and a simplified deployment model. Built for scalability and large-scale games, it's a serverless technology designed for modern applications.

https://spacetimedb.com/

Clickbench Says Postgres Is a Great Analytics Database

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Clickbench ranks Postgres highly for analytics after optimization via pg_mooncake. Unlike traditional views of Postgres as an OLTP database, its extensibility allows it to perform comparably to specialized analytics systems. Key advancements include using a columnstore format and vectorized execution with embedded DuckDB for efficient data processing. This new capability retains Postgres's flexibility while streamlining the data stack.

https://www.mooncake.dev/blog/clickbench-v0.1

Why Local-First Software Is the Future and Its Limitations

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Local-first software keeps user data primarily on the client side, enhancing performance, privacy, and offline usability. It's gaining traction due to improved browser storage limits, new APIs for efficient file management, and advances in tools like RxDB. While offering advantages like reduced server load and instantaneous user experiences, local-first also faces challenges in data synchronization, conflict resolution, and eventual consistency, making it less suitable for large datasets or applications requiring immediate data integrity. Overall, it presents a promising yet complex paradigm shift in software design.

https://rxdb.info/articles/local-first-future.html

VectorChord-BM25: Revolutionize PostgreSQL Search With BM25 Ranking

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VectorChord-BM25 enhances PostgreSQL full-text search via BM25 ranking, outperforming ElasticSearch in speed (3x faster) while maintaining accuracy. Key features include optimized indexing, enhanced tokenization, and relevant scoring, making it ideal for various applications. The implementation focuses on integrating BM25 scoring natively in PostgreSQL, contrasting with other solutions like ParadeDB, which may face compatibility issues. Future developments aim to enhance tokenization for better multilingual support. Overall, VectorChord-BM25 sets a new standard for efficient, relevance-based searches in PostgreSQL.

https://blog.vectorchord.ai/vectorchord-bm25-revolutionize-postgresql-search-with-bm25-ranking-3x-faster-than-elasticsearch

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