Best of PostgreSQL — June 2024

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   Video

   developedbyed·2y

   Learn SQL Super Fast - Tutorial from absolute scratch

   This tutorial covers the setup of PostgreSQL from scratch, including creating databases, tables, and SQL joins. It emphasizes the importance of fundamental technologies like SQL over rapidly changing frameworks. You'll learn to install PostgreSQL, create databases and tables, use SQL commands to manage data, and understand SQL joins and foreign keys for relational data. The tutorial also briefly discusses the limitations of ORMs in the JavaScript ecosystem and the value of mastering core technologies.

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2. 2
   Article

   Community Picks·2y

   PostgreSQL Primary Key Dilemma: UUID vs. BIGINT

   Learn how to optimize your PostgreSQL database by addressing challenges with primary keys, including slower INSERT performance with random UUIDs, storage space impact, and index selection.

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   Article

   Community Picks·2y

   How to upload to S3 in Next.js and save references in Postgres

   Learn how to add a feature to a Next.js app that allows users to upload files to Amazon S3 using presigned URLs, and save references to these files in a Postgres database. The guide covers creating a Neon project, setting up an S3 bucket, creating IAM user access keys, and setting up a Next.js application with necessary API routes to handle file uploads and database operations.

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   Article

   freeCodeCamp·2y

   How to Create Database Migrations in Go Using Docker and Postgres

   Learn how to create and manage database migrations in Go using Docker and Postgres. This guide covers setting up a Docker container, creating a schema with TablePlus, installing golang-migrate, generating migration scripts, and running migrations effectively.

   41

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   Article

   Hacker News·2y

   danvergara/dblab: The database client every command line junkie deserves.

   dblab is a fast and lightweight interactive terminal-based UI application for PostgreSQL, MySQL, and SQLite3. It can be easily installed and supports cross-platform usage. It provides a range of features for working with local or remote databases.

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   Article

   Towards Data Science·2y

   How I Dockerized Apache Flink, Kafka, and PostgreSQL for Real-Time Data Streaming

   Achieve seamless integration of Apache Flink, Kafka, and PostgreSQL using Docker-Compose, leveraging pyFlink for real-time data processing. This guide provides practical tips, configures Flink in session mode, and demonstrates how to create custom Docker images for pyFlink to ensure Python jobs run smoothly. Additionally, the post covers setting up Kafka topics, creating Postgres tables, and handling sensor data streams. Follow the step-by-step guide to build and experiment with a streaming pipeline that efficiently processes and stores data.

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   Article

   Lobsters·2y

   Serving a billion web requests with boring code

   A developer recounts their experience building and launching a large-scale healthcare application for the US government using stable and well-known technologies like Golang, PostgreSQL, and React. Emphasizing the importance of simplicity and reliability, the project achieved high performance with minimal errors. The backend was modular, using gRPC for service communication, and a strict backwards-compatibility policy ensured robustness. The team faced challenges with documentation generation and maintaining sql-mock tests, but overall, the software was successful and served millions efficiently.

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   Article

   Community Picks·2y

   Postgres is all you need, even for vectors

   Explore the versatility of using Postgres for vector storage and querying with the pgvector extension. Learn about the performance and cost advantages compared to other databases. Discover how Postgres can be used for knowledge graphs and hybrid search.

   30

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9. 9
   Article

   eBPF·2y

   Monitoring PostgreSQL Database on Kubernetes using eBPF

   Learn how to monitor PostgreSQL databases on Kubernetes using eBPF. The post covers the theoretical background and includes a practical example demonstrating how to track client queries to identify potential database bottlenecks. The monitoring system employs an eBPF agent to observe and analyze protocol message formats without requiring modifications to the application code. It concludes with a performance evaluation highlighting the impact on latency and CPU load.

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    Article

    DEV·2y

    Comparing SQL engines by CPU instructions for DML

    This post compares the CPU usage of different SQL engines, such as PostgreSQL, Oracle, SQL Server, MySQL, TiDB, YugabyteDB, and CockroachDB, for simple DML operations. The results show that despite their different implementations, PostgreSQL, Oracle, and SQL Server perform well in terms of CPU usage. TiDB, YugabyteDB, and CockroachDB exhibit higher CPU utilization due to their distributed and scalable architectures. Overall, the performance varies depending on the database engine and workload.

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    Article

    TigerData (Creators of TimescaleDB)·2y

    Postgres: The Birdhorse of Databases

    PostgreSQL is a unique and successful database that appeals to both traditional enterprises and cloud-native startups. Its extension framework allows for flexibility and easy addition of functionality. PostgreSQL is considered the most popular database among professional developers.

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    Article

    The New Stack·2y

    PostgreSQL vs. MongoDB: Which Is Better for GenAI?

    Generative AI (GenAI) requires databases that can efficiently handle complex, large-scale data structures. This post compares PostgreSQL and MongoDB for GenAI workloads, highlighting that MongoDB, with its BSON format, offers superior performance for large documents and multiple attributes versus PostgreSQL's JSON/JSONB handling. Specific benchmarks in write and read operations underscore how PostgreSQL struggles with large payloads, whereas MongoDB maintains consistent performance, making it a better choice for GenAI tasks.

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    Article

    Pamela Fox·2y

    pgvector for Python developers

    Learn about vector embeddings, how to use pgvector with PostGreSQL, and perform similarity and searching with pgvector in Python.

    19

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    Article

    Community Picks·2y

    Using LlamaIndex with Postgres to Build your own Reverse Image Search Engine

    Learn to build a reverse image search engine using Astro, LlamaIndex, and serverless Postgres. The guide covers creating vector embeddings with ClipEmbeddings, setting up a server-side Postgres database, and deploying the application on Vercel. You'll create API endpoints for indexing and searching images and build a user interface to interact with the search functionality.

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    Article

    Hashrocket·2y

    Generated Columns in PostgreSQL

    Generated columns in PostgreSQL, introduced in version 12, allow data to be computed dynamically at the database level. There are two types: virtual and stored, though PostgreSQL only supports stored columns. This post provides an example of creating and using a generated column, explores when they are computed, and highlights some limitations, such as the inability to reference a generated column from another generated column and the use of constraints on generated columns.

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