NewApp Digest
search bot

partitioning

PostgreSQL 13’s Sunset: Why Database Pros Must Upgrade Before the Lights Go Out
Tech Optimizer
November 7, 2025

PostgreSQL 13’s Sunset: Why Database Pros Must Upgrade Before the Lights Go Out

Organizations using PostgreSQL 13 must upgrade before its end-of-life on November 13, 2025, as this will result in the cessation of security patches, bug fixes, and official support. Continuing to use an unsupported version exposes systems to vulnerabilities, which can lead to data breaches and compliance challenges. The last minor release for PostgreSQL 13 was 13.21 in May 2025. Upgrading to newer versions, such as PostgreSQL 16 or 17, offers performance improvements and enhanced features. Strategies for upgrading include using tools like pg_upgrade, pg_dump/pg_restore, and logical replication to minimize downtime. Compatibility issues may arise due to deprecated functions in PostgreSQL 13, necessitating code reviews. Managed services like those from Percona can provide support beyond EOL. The costs of not upgrading can be significant, with potential downtime from security breaches often exceeding migration expenses.
Meet the Team Behind Snowflake Postgres
Tech Optimizer
November 2, 2025

Meet the Team Behind Snowflake Postgres

In June 2025, Snowflake acquired Crunchy Data to integrate Postgres into its offerings. Crunchy Data, founded in 2012, focused on enhancing Postgres for enterprise environments, creating a security-first distribution called Crunchy Certified PostgreSQL. They introduced the Postgres Operator for Kubernetes in 2017 and launched Crunchy Bridge, a fully managed cloud Postgres service, in 2020. The Crunchy Data team has made significant contributions to the Postgres ecosystem, including enhancements to core functionality and extensions like PostGIS and pg_partman. Key team members have held leadership roles in the PostgreSQL community. Snowflake Postgres aims to unify transactional and analytical workloads, allowing organizations to run applications at scale while leveraging data for analytics, machine learning, and AI.
How to switch your Windows 10 PC to Linux Mint - for free
Winsage
October 5, 2025

How to switch your Windows 10 PC to Linux Mint – for free

The countdown for Windows 10 support is underway, prompting users to consider alternatives like Linux Mint, especially if they are hesitant about upgrading to Windows 11 or if their hardware does not meet the requirements. Linux has become more user-friendly, and Linux Mint is recommended for both newcomers and experienced users. To switch to Linux Mint, users need a Windows PC, an internet connection, and a USB stick with at least 4GB of storage, with an estimated installation time of about 2 hours. Users should compile a list of essential programs and check for Linux-compatible alternatives. Many cloud-based applications work on Linux, and Windows 10 can be run within Linux using Oracle VirtualBox for incompatible programs. The installation process involves downloading the Linux Mint ISO from the website, preparing a USB drive, and adjusting the boot order in the BIOS/UEFI settings. Users should disable Secure Boot to ensure a smooth installation. After rebooting, the Mint interface will appear, and the installation wizard will guide users through the setup process, including language preferences and partitioning the hard drive. Enabling Timeshift for system backups and using the Backup Tool for personal files is recommended. After installation, users should check for additional drivers and install multimedia codecs. Linux Mint requires a minimum of 2GB of RAM and 20GB of disk space and is compatible with most modern hardware. Running both Linux Mint and Windows on the same PC is possible, either by dual-booting or using a virtual machine. Most modern hardware is compatible with Linux, and testing Mint through a live session on a USB stick can confirm compatibility. Software-as-a-service applications generally work well on Linux, while older programs may require additional tools. Many popular applications are available on Linux, and Steam-based games perform well.
How to enable TPM, Secure Boot, HVCI, and VBS for Battlefield 6 and Black Ops 7
AppWizard
October 1, 2025

How to enable TPM, Secure Boot, HVCI, and VBS for Battlefield 6 and Black Ops 7

Battlefield 6 requires gamers to meet advanced security requirements to access the game, including TPM 2.0, Secure Boot, HVCI, and VBS. TPM 2.0 is a hardware-based security feature found on most modern motherboards, and if absent, users may need to research their motherboard for upgrade options. Secure Boot and TPM 2.0 can be checked using the Steam beta client or through the Device Manager and System Information panel. If disabled, they can typically be enabled via the BIOS/EFI system. Windows must operate in UEFI mode with the GUID partition table for these features to function correctly, and if installed in legacy mode, reinstallation may be necessary. HVCI protects against malicious code and can be checked via the memory integrity settings. VBS can be verified through the System Information panel, indicating if it is running.
Global indexes for partitions in Postgres Pro: uniqueness without hacks
Tech Optimizer
September 23, 2025

Global indexes for partitions in Postgres Pro: uniqueness without hacks

Partitioning in PostgreSQL divides large tables into smaller segments called partitions, improving query performance by enabling partition pruning, which allows the DBMS to scan only relevant partitions. However, local indexes on partitioned tables have limitations, such as inability to enforce global uniqueness and inefficiencies when querying across multiple partitions. Global indexes, introduced in Postgres Pro Enterprise, operate at the partitioned table level, ensuring global uniqueness and improved query performance. They are created for the entire table and include data from all partitions, allowing for faster queries but slower writes due to uniqueness checks. Global indexes do not automatically remove entries for deleted rows and require manual VACUUM to clean up obsolete entries. Current limitations include lack of support for concurrent operations, expressions in index creation, and certain foreign key constraints. Despite these limitations, global indexes can enforce global uniqueness and enhance query performance for non-partitioning keys.
How we loaded a petabyte into PostgreSQL before New Year — and what happened next
Tech Optimizer
August 26, 2025

How we loaded a petabyte into PostgreSQL before New Year — and what happened next

A team decided to test PostgreSQL's capabilities with a one-petabyte database, setting a challenge for December 10, with a report due by January 20. They initially sought cloud storage but found no provider could meet their requirement for a single chunk of storage, leading them to rent physical servers. They used Shardman, a distributed database engine, to manage the database across seven servers. They employed the YCSB benchmark for performance testing and faced various challenges, including data loading issues and hardware problems. By January 15, they reached 863 terabytes of data generation, falling short of their petabyte goal, and documented their findings for future reference.
silver Android smartphone
Tech Optimizer
August 5, 2025

Building a job search engine with PostgreSQL’s advanced search features

Job search platforms connect employers and candidates through advanced search engines that analyze structured and unstructured data. These platforms require robust database technologies for executing complex queries, full-text and semantic searches, and geospatial functionalities. A modern job search engine consists of a data repository that stores job listings and candidate profiles, and a search engine that facilitates bidirectional searches. Key features of an effective job search engine include: - **Full-text search**: Provides lexical matching for job titles and skills, supporting exact phrase matching and typo-tolerant searches. - **Semantic search**: Uses vector-based similarity to understand context and relationships beyond literal terms. - **Geospatial search**: Incorporates geographic considerations to find opportunities within specific distances. PostgreSQL serves as both a data repository and search engine, supporting full-text search, semantic search via the pgvector extension, and geospatial queries using the PostGIS extension. The job search engine utilizes PostgreSQL to manage job listings and candidate profiles, enabling real-time searches across millions of entries. The data model for a job search engine includes tables for jobs and resumes, with columns for full-text search vectors, semantic vectors, and geographical locations. PostgreSQL's full-text search capabilities include tokenization, dictionaries for language-aware parsing, and ranking functions for relevance. Advanced features such as proximity search, simple and weighted ranking, and fuzzy matching enhance search accuracy. Vector embeddings represent text in high-dimensional space, allowing for semantic searches that recognize similar roles or skills. PostgreSQL supports vector similarity searches with specialized indexing methods like IVFFlat and HNSW for efficient querying. Geospatial search capabilities in PostgreSQL enable location-aware job searches, allowing candidates to find jobs within commuting distances. Combining different search techniques, such as full-text and semantic searches, provides more relevant results. Performance optimization features in PostgreSQL address challenges related to computational complexity, indexing overhead, and concurrent query loads. The architecture discussed is applicable to various applications beyond job search platforms, including e-commerce, real estate, content recommendation systems, travel, and healthcare provider matching.
Search