data processing Archives

Tech Optimizer

December 4, 2025

Optimizing Postgres Pro for 1C: what’s new

Postgres Professional has released Postgres Pro Enterprise 17.6, which includes enhancements for 1C users. Key features include: - Official documentation for configuring Postgres Pro with 1C solutions, consolidating best practices for performance tuning and cluster operation. - Suppression of excessive catalog cache invalidation messages during index creation or dropping on temporary tables and statistics gathering. - Introduction of the skip_temp_rel_lock parameter to bypass lock acquisition for temporary relations and their indexes, improving performance during frequent DDL operations. - Reengineered TRUNCATE operations for temporary tables, allowing for a single scan of the buffer pool, enhancing efficiency. - Improved substring search performance in 1C applications by enabling accurate cost estimation for LIKE operators on mvarchar fields. - Memoization support for parameterized ANTI JOIN nodes, reducing unnecessary data processing cycles in complex queries. - Reduced lock requests during query planning involving multiple relations, improving operation when new sessions connect. - Optimized VACUUM ANALYZE on catalog tables, ensuring the pg_internal.init file remains intact during analysis, allowing for swift new session connections.

Winsage

November 18, 2025

Microsoft just revealed how Windows 11 is evolving into an agentic OS — finally the explanation we’ve all been waiting for

Microsoft has introduced a new support document detailing the transformation of Windows 11 into an agentic operating system, emphasizing AI-native capabilities that allow the PC to autonomously manage tasks. A new experimental feature, agent workspace, will soon be available in a private developer preview for Windows Insiders. This feature enables AI to run applications in parallel with the user, designed to be lightweight and secure, with scalable memory and CPU usage. Microsoft has identified three core security pillars for agentic OS experiences: non-repudiation, confidentiality, and authorization. Additionally, essential security principles for AI agents include autonomy, activity logging, user supervision, least privilege, and defined data processing purposes. Microsoft plans to integrate these capabilities into Windows 11, with applications like Copilot Actions being among the first to utilize them, and third-party developers will also be able to create their own AI agents using the provided framework.

Tech Optimizer

November 17, 2025

Introducing pg_lake: Integrate Your Data Lakehouse with Postgres

pg_lake is a tool developed by the team at Crunchy Data, now part of Snowflake, that provides a native Postgres experience for working with open data lakehouse formats like Iceberg and Parquet. The initiative began with the launch of Crunchy Bridge for Analytics over 18 months ago, aimed at addressing the fragmentation of data between Postgres databases and object storage. The decision to open source pg_lake is intended to establish a standard for the Postgres ecosystem, empower developers to create modern applications, and demonstrate Snowflake's commitment to enhancing Postgres capabilities. pg_lake is now available for exploration and use by developers.

Tech Optimizer

October 29, 2025

Inside the race to build agent-native databases

A disconnect has been identified between traditional databases and the requirements of AI agents, prompting a rethinking of database architecture. Four initiatives are redefining databases for AI: 1. **AgentDB** treats databases as lightweight, disposable artifacts, allowing agents to create and discard databases easily for single tasks, catering to simple AI applications and temporary data processing needs. It is not suitable for complex transactional systems. 2. **Postgres for Agents** enhances PostgreSQL with features like zero-copy forking, enabling secure testing and experimentation without affecting live systems. It targets developers building AI applications and offers a cloud service with a free tier. 3. **Databricks Lakebase** integrates transactional capabilities within a data lakehouse architecture, providing seamless access to real-time operational data and historical insights for AI agents. It aims to unify data workloads and reduce the complexity of maintaining separate databases. 4. **Bauplan Labs** focuses on safety and reliability, developing a "programmable lakehouse" with a "Git-for-data" model that ensures verifiable and auditable data operations for AI agents. It targets high-stakes scenarios where mistakes could have significant repercussions. These initiatives reflect a broader trend of reshaping databases to cater to machines, emphasizing ephemeral, isolated, and context-aware systems.

AppWizard

October 15, 2025

Researchers expose critical Android flaw allowing apps to steal sensitive data

Security researchers have identified a data theft technique called Pixnapping that exploits vulnerabilities in Android devices, specifically targeting sensitive information from various applications without needing special permissions. This method allows malicious apps to capture data from other apps or websites, including sensitive information from platforms like Google Maps, Gmail, Signal, Venmo, and two-factor authentication codes from Google Authenticator. The technique utilizes a hardware side channel known as GPU.zip to read screen pixel data by measuring rendering times. The data leak rate is between 0.6 to 2.1 pixels per second, sufficient to reconstruct sensitive information. The vulnerability is designated as CVE-2025-48561 and affects Android versions 13 through 16, including devices like the Pixel 6 to 9 and Galaxy S25. A partial patch was released in September 2025, with a comprehensive solution expected in December. The attack allows benign applications from the Google Play Store to potentially spy on sensitive on-screen data, highlighting broader concerns regarding side-channel vulnerabilities that arise from hardware data processing rather than software bugs. While Google has stated there is no evidence of exploitation currently, the existence of this attack suggests that malware could bypass traditional security measures. Google is working on additional fixes to limit misuse of the blur API and improve detection capabilities, but the underlying GPU.zip vulnerability remains unresolved. Users are advised to avoid untrusted apps and keep their devices updated, as more side-channel attacks similar to Pixnapping may emerge in the future.

Winsage

October 14, 2025

Microsoft previews People grouping in OneDrive photos

Microsoft is introducing an AI-driven feature in OneDrive that allows users to group photos based on recognized faces. Currently in a mobile preview for select users, the feature requires manual identification of faces and has limitations on user control, allowing toggling of the People section only three times a year. Microsoft has not clarified the reasoning behind this limitation. The company acknowledges that certain regions require user consent for photo processing, which may lead to regulatory scrutiny. If users disable the facial grouping feature, associated data will be erased within 30 days. Microsoft claims it does not use facial scans or biometric data for AI training, but concerns about privacy remain.

AppWizard

October 10, 2025

Google Docs Android App Integrates Gemini AI ‘Help Me Write’ Feature

Google is enhancing its Google Docs app on Android with the introduction of the "Help me write" feature, powered by the Gemini AI model. This feature, which has been available on web versions of Docs and Gmail, is currently in development and includes a new toolbar icon for submitting writing requests. Although not fully operational yet, it aims to improve mobile productivity by allowing users to generate and refine text. The feature may also integrate with existing Gemini capabilities like summarization and rephrasing. The rollout faces challenges, including privacy concerns related to data processing and the need for effective language support, with plans for Gemini to be available in over 20 languages by June 2025. Access may require a Workspace or AI premium plan, and a full launch is anticipated by late 2025. This advancement could significantly impact mobile workflows in industries such as journalism and marketing, enhancing collaboration and document creation.

Tech Optimizer

October 3, 2025

From Postgres to ScyllaDB: How Coralogix Achieved 349x Faster Queries

A new technology leveraging artificial intelligence is emerging to enhance efficiency and accuracy in data processing across various industries. By integrating machine learning algorithms with existing systems, organizations can analyze vast amounts of data in real-time, leading to informed decision-making and improved operational performance. This technology automates routine tasks, allowing human resources to focus on strategic initiatives, streamlines processes, reduces human error, and can be customized to meet specific industry needs. Companies are experiencing significant improvements in productivity and customer satisfaction as a result. The ongoing advancement of AI is expected to lead to greater integration into business operations and the development of new business models that utilize data in innovative ways.

AppWizard

September 29, 2025

A working ChatGPT chatbot has been built inside Minecraft

A Minecraft enthusiast named sammyuri created a functioning AI language model within the game, capable of basic conversations, using approximately five million parameters. The model was trained externally and integrated into Minecraft through redstone circuits, without the use of mods, command blocks, or datapacks. This project showcases the potential of redstone technology, as sammyuri connected millions of logical pathways to mimic a machine learning model's data processing capabilities. Although the conversations are slow and limited to basic interactions, this achievement highlights the possibility of machine learning in Minecraft.

Tech Optimizer

September 25, 2025

Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1

The project involves creating a dynamic video game recommender system using PostgreSQL, FastAPI, and Render, which recommends games based on user interactions. It utilizes data from Steam's API, with a dataset of approximately 2000 games. The system architecture includes a PostgreSQL database and a FastAPI layer for data processing. Key components include a Game Table, User Table, User_Game Table, Game_Tags Table, and User_Recommendation Table. FastAPI is used to create APIs for data access and updates, while a recommendation pipeline generates suggestions based on user preferences using content-based filtering techniques. The project is divided into two parts: setup and theoretical foundations, and deployment. The system is deployed on Render for accessibility.