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Google's analytical October Workspace Drop simplifies data in Sheets, bolsters AI security
AppWizard
November 1, 2025

Google’s analytical October Workspace Drop simplifies data in Sheets, bolsters AI security

Google has released updates for its Workspace suite in October, enhancing data comprehension, structure, and formatting in Sheets through Gemini AI. Key features include improved understanding of complex instructions for data manipulation. Google Drive has introduced a ransomware detection feature for desktop users, which alerts them to suspicious activity and pauses data synchronization. Gmail now includes end-to-end encryption for emails to enhance privacy and security. These updates build on August's enhancements, which featured file summaries for Chat, Video Overviews for NotebookLM, and the Veo 3 model in the Vids app, with the recent transition to Veo 3.1 providing greater creative control, improved sound capabilities, and more realistic textures.
How Distributed Postgres Solves Cloud's High-Availability Problem
Tech Optimizer
September 11, 2025

How Distributed Postgres Solves Cloud’s High-Availability Problem

Application availability and downtime are significant concerns for organizations, with unplanned outages costing the Global 2000 approximately billion annually, averaging million in losses per company. High-stakes sectors like healthcare and finance face severe financial repercussions from even brief outages. Phillip Merrick, co-founder and CEO of pgEdge, highlights that five minutes of downtime in a trading platform can lead to millions lost. Many organizations still host applications within a single cloud region, which poses risks, as evidenced by incidents like the 2021 AWS Tokyo outage and the 2023 Google Cloud outage. A survey indicated that 21% of IT decision-makers experienced a cloud region failure in the past year. The urgency for high availability has increased due to rising consumer expectations, yet many industries still rely on outdated practices that can lead to downtime. Keeping data synchronized across multiple regions is challenging, particularly for PostgreSQL, which requires continuous data synchronization for instant failover. pgEdge offers a distributed Postgres architecture that enables multimaster, multiregion deployments with real-time data replication, addressing high availability needs. Organizations using this architecture, including a global investment management firm, benefit from enhanced service continuity amid cloud outages.
We’ve learned how to migrate databases from Oracle to Postgres Pro at 41 TB/day
Tech Optimizer
August 19, 2025

We’ve learned how to migrate databases from Oracle to Postgres Pro at 41 TB/day

An organization transitioning from Oracle Database to Postgres Pro faces challenges such as slow data transfer, the need to keep the source system operational during migration, and risks of data loss or corruption. ProGate is a toolkit developed to simplify this migration process, consisting of three main components: 1. **ProCopy**: A utility for high-speed initial data loading, achieving speeds of 200–500 MB/sec for Oracle to Postgres Pro migrations and around 1 GB/sec for PostgreSQL to Postgres Pro migrations. It allows for parallel execution, column omission, renaming, and on-the-fly data type modifications. 2. **ProSync**: A tool for continuous change synchronization (CDC) that captures and applies changes from Oracle to Postgres Pro in real-time, minimizing downtime during migration. 3. **ProCheck**: A tool that verifies data quality and integrity post-migration by comparing tables, rows, and columns across both databases to identify discrepancies. ProGate is designed for extensive databases, supports hot migrations with minimal downtime, and ensures strict data consistency. Limitations include potential manual intervention for schema changes, specific mapping for custom data types, and effectiveness issues with tables lacking primary keys. The public release of ProGate is planned for this fall, with future enhancements including a graphical user interface and support for additional database sources.
Scaling AI Inference at the Edge With Distributed PostgreSQL
Tech Optimizer
July 21, 2025

Scaling AI Inference at the Edge With Distributed PostgreSQL

Data is crucial for artificial intelligence, especially for inference workloads used in real-time decision-making across various platforms. Traditional centralized cloud-based AI inference struggles with demands for low latency and high availability, particularly in applications like autonomous vehicles and healthcare. Shifting AI inference to the edge reduces latency, enhances data privacy, and lowers bandwidth costs. Antony Pegg emphasizes the need for a multi-master active-active architecture that allows read and write operations at any node, ensuring data synchronization and high availability. Misconceptions about edge AI include beliefs that edge hardware can't handle AI workloads, that edge inference is limited to low-stakes use cases, and that centralized systems are necessary for data integrity. The shift to distributed inference can lead to reduced latency, faster insights, and lower costs, while supporting data compliance with regulations. Companies are adopting distributed PostgreSQL solutions with multi-master architecture for low latency and high availability. Enquire AI is an example of a company that improved performance and compliance by transitioning to pgEdge Cloud. This architecture allows for consistent data availability and supports scalable AI solutions at the edge.
ParadeDB Raises Funds, Challenges Elasticsearch with Postgres Integration
Tech Optimizer
July 16, 2025

ParadeDB Raises Funds, Challenges Elasticsearch with Postgres Integration

Postgres, an open-source database management system, is experiencing a revival due to its compatibility with AI applications and its ability to manage structured data effectively. Despite its strengths, Postgres lacks native high-performance full-text search and analytics capabilities, leading organizations to use separate systems like Elasticsearch, which complicates data management. ParadeDB, an open-source extension developed in 2023, addresses these limitations by enabling sophisticated data search and analytics directly within Postgres, eliminating the need for data transfers. ParadeDB has gained traction, securing its first enterprise customer by early 2024 and recently completing a funding round for platform enhancements. Its integration with Postgres simplifies workflows and reduces operational overhead, making it a compelling alternative to traditional search solutions.
New Windows 11 trick will improve your Galaxy Book's battery life
Winsage
July 15, 2025

New Windows 11 trick will improve your Galaxy Book’s battery life

Microsoft is testing a new feature called Adaptive Battery Saver Mode for Windows 11 devices, which adjusts battery usage based on workload rather than just battery level. Unlike traditional Energy Saver mode, it maintains screen brightness and allows background tasks to continue without interruption. This feature is currently being tested in the Canary Channel under build number 27898, and if successful, it will be rolled out to all Windows 11 devices. The development coincides with advancements in power-efficient processors from AMD, Intel, and Qualcomm, aimed at improving battery performance in Windows laptops.
Query Amazon Aurora PostgreSQL using Amazon Bedrock Knowledge Bases structured data
Tech Optimizer
July 9, 2025

Query Amazon Aurora PostgreSQL using Amazon Bedrock Knowledge Bases structured data

Amazon Bedrock Knowledge Bases has introduced a fully managed Retrieval Augmented Generation (RAG) feature that connects large language models (LLMs) with internal data sources, enhancing the relevance and accuracy of responses by integrating contextual information from private datasets. During AWS re:Invent 2024, it was announced that this feature now supports natural language querying for structured data retrieval from Amazon Redshift and Amazon SageMaker Lakehouse, allowing generative AI applications to access both structured and unstructured data sources. The system converts user queries into SQL queries using natural language processing, enabling data retrieval without requiring users to know SQL syntax. Amazon Bedrock Knowledge Bases currently supports structured data retrieval from Amazon Redshift and SageMaker Lakehouse. Although direct support for Aurora PostgreSQL-Compatible is not available, users can utilize zero-ETL integration between Aurora PostgreSQL-Compatible and Amazon Redshift to make their data accessible. This integration replicates Aurora PostgreSQL tables to Amazon Redshift in near real-time, simplifying data management. To enable natural language querying of structured application data stored in Aurora, organizations can set up an Aurora PostgreSQL database, create a schema with interconnected tables (products, customers, and orders), and populate these tables with sample data while maintaining referential integrity. Subsequently, they can establish zero-ETL integration with Amazon Redshift, which involves creating a Redshift Serverless workgroup and mapping the database for synchronization. Once the zero-ETL integration is verified, organizations can create an Amazon Bedrock knowledge base for natural language querying. This requires granting appropriate permissions to the Amazon Bedrock Knowledge Bases AWS Identity and Access Management (IAM) role and ensuring the knowledge base is synchronized with Amazon Redshift. After setting up the knowledge base, users can execute natural language queries, which are translated into SQL and processed to generate human-readable responses. Examples of queries include counting unique customers and identifying customers who have purchased the most products. Finally, it is recommended to clean up resources after use to avoid ongoing charges.
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