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Windows 11 File Explorer Lag: Legacy XP Feature Fix via Registry Tweak
Winsage
January 12, 2026

Windows 11 File Explorer Lag: Legacy XP Feature Fix via Registry Tweak

File Explorer in Windows 11 has been reported to have performance issues, particularly delays when navigating folders with many media files or documents. This problem is linked to the auto-discovery feature, which optimizes folder display settings based on content but incurs a significant computational burden. Disabling this feature through registry modifications can lead to improved performance, with users experiencing faster navigation and reduced folder load times. Microsoft has acknowledged these issues and plans to preload File Explorer for quicker launches, but the underlying problems remain largely unaddressed. Users have shared their experiences and solutions, including registry tweaks that set folder types to "NotSpecified" to eliminate scanning overhead. Despite some incremental updates from Microsoft, many users still face core lags, prompting ongoing community-driven fixes and discussions about the need for deeper audits of legacy code.
Microsoft Optimizes Windows 11 File Explorer to Slash RAM Usage
Winsage
December 28, 2025

Microsoft Optimizes Windows 11 File Explorer to Slash RAM Usage

Microsoft is addressing criticism regarding Windows 11's File Explorer performance, particularly its excessive RAM consumption during searches. The company is testing optimizations aimed at reducing memory usage while maintaining speed, originating from an Insider Preview build. These changes involve eliminating duplicate indexing tasks, which could lead to a 20-30% reduction in RAM usage during intensive search sessions. Additionally, the update includes a streamlined context menu in File Explorer to enhance usability. Insider feedback has been positive, with users reporting smoother performance across various devices. The optimizations may also improve system stability and scalability in enterprise environments. However, some users express skepticism about whether these fixes are temporary solutions to deeper architectural issues. The full benefits of the update are expected to materialize once it reaches general availability, anticipated in early 2026.
Microsoft tests File Explorer search optimisation to reduce RAM usage in Windows 11
Winsage
December 28, 2025

Microsoft tests File Explorer search optimisation to reduce RAM usage in Windows 11

Microsoft is enhancing the Windows 11 File Explorer to reduce its memory usage, currently being tested in Windows 11 Build 26220.7523 and above for Insider preview participants. The updates aim to optimize search functionality by eliminating duplicate file indexing operations, which have historically caused high RAM and CPU consumption. Additionally, Microsoft is refining the File Explorer interface by relocating less frequently used options in the right-click context menu into a dedicated sub-menu, labeled either “Manage file” or “Other actions.” A broader rollout of these updates is expected around late January or February.
Microsoft says Windows 11 File Explorer will soon use less RAM when you search files
Winsage
December 26, 2025

Microsoft says Windows 11 File Explorer will soon use less RAM when you search files

Windows 11 is updating its File Explorer to improve search efficiency and reduce memory usage during file searches, currently being tested in Windows 11 Build 26220.7523 for Windows Insider participants. The new search functionality eliminates duplicate file indexing operations, resulting in faster searches and lower system resource usage. The File Explorer Search relies on the Windows Search Indexer, which will now avoid redundant indexing, leading to reduced disk I/O, lower CPU cycles, and decreased RAM usage. Additionally, Microsoft is decluttering the context menu by relocating features like “Compress to” and “Copy as path” into a new sub-menu called “Manage file,” or “Other actions” on different machines. These updates are expected to be rolled out by the end of January or in February.
Biscuit PostgreSQL Extension Accelerates LIKE Queries with Roaring Bitmaps
Tech Optimizer
December 22, 2025

Biscuit PostgreSQL Extension Accelerates LIKE Queries with Roaring Bitmaps

Biscuit is an open-source project developed by CrystallineCore, available on GitHub, that introduces a specialized index access method for PostgreSQL to enhance query speed for pattern matching in LIKE queries. It addresses limitations of traditional indexing methods like B-tree and GIN indexes, particularly in complex LIKE or ILIKE operations and multi-column searches. Biscuit uses in-memory bitmap structures to reduce query times by precomputing bitmap representations of string patterns, allowing for rapid filtering without scanning entire rows. The project has a vibrant community contributing to its optimization and performance improvements, especially for ARM architectures. Independent tests show that Biscuit can outperform PostgreSQL's pg_trgm by factors of 5-10x on wildcard-heavy workloads. Real-world applications include significant reductions in query latencies for e-commerce and log processing pipelines, with a reported 40% reduction in ETL job times for error pattern detection in server logs. Biscuit faces challenges such as the initial time required to build indexes on large tables and limited compatibility with older PostgreSQL versions, but the maintainers are actively addressing these issues. The design of Biscuit encourages integration with other open-source tools, and community feedback is shaping its future development.
Watch Out Elasticsearch! Tiger Data's PostgreSQL BM25 Search Extension Goes Open Source
Tech Optimizer
December 20, 2025

Watch Out Elasticsearch! Tiger Data’s PostgreSQL BM25 Search Extension Goes Open Source

Tiger Data has released pg_textsearch as an open-source extension under The PostgreSQL License on GitHub, previously exclusive to Tiger Cloud. This extension allows developers to perform BM25 relevance-ranked keyword searches directly within PostgreSQL, eliminating the need for external search systems like Elasticsearch. Notable features of pg_textsearch include support for 29+ languages, compatibility with partitioned tables, intuitive SQL syntax, a memtable architecture for optimized indexing, and adjustable BM25 ranking parameters. Tiger Data aims to develop a comprehensive Postgres Search Stack that integrates keyword and vector search capabilities.
Agentic Postgres: Postgres for Agentic Apps with Fast Forking and AI-Ready Features
Tech Optimizer
December 12, 2025

Agentic Postgres: Postgres for Agentic Apps with Fast Forking and AI-Ready Features

Tiger Data has launched Agentic Postgres, a database solution built on Postgres for AI agents and developers. It features rapid forking capabilities, a multi-channel processing (MCP) server, and native support for BM25 and vector searches via a command-line interface (CLI). The MCP server allows users to interact with agents through high-level prompts for tasks like schema design. Agentic Postgres includes two advanced plugins to enhance search functionalities: an upgraded pgvectorscale for improved indexing and pg_textsearch for BM25 keyword ranking. The core of the platform is Fluid Storage, a distributed storage system that enables rapid, zero-copy forks of production data. Tiger Data highlights the importance of fluidity in database management for agentic software, which requires quick scaling and modifications. The growing needs of developers for integrated solutions reflect a shift due to AI advancements. Competitors in the market include Firebolt, Weaviate, and Qdrant. A free tier for Agentic Postgres is available, offering access to various features with limitations.
PostgreSQL 12 progress update
Tech Optimizer
December 6, 2025

PostgreSQL 12 progress update

The PostgreSQL development team provided a progress update on PostgreSQL 12, highlighting several enhancements: - Just-in-Time (JIT) compilation will be enabled by default, reducing memory consumption during COPY operations and function calls, and improving search performance for multi-byte characters. - Server configuration improvements will allow enabling/disabling cluster checksums via pg_checksums, reduce the default value for autovacuum_vacuum_cost_delay to 2ms, and support micro-seconds for time-based server variables. - Speed improvements for btree index insertions will enhance space efficiency of page splits, reducing locking overhead and optimizing performance for UPDATEs and DELETEs with many duplicates. - Recovery parameters can be modified during reloads, including archive_cleanup_command, promote_trigger_file, recovery_end_command, and recovery_min_apply_delay, along with a new streaming replication timeout feature. - The peculiar behavior of OID columns will likely be phased out, but they will still be defined as type OID, requiring adjustments for operations on tables with OID-named columns. - Data types such as abstime, reltime, and tinterval are expected to be removed. - Enhancements to geometric functions and operators will improve results, and geometric types will be restructured to manage NaN, underflow, overflow, and division by zero scenarios.
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