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Googlebook review: Android on a laptop is still Android
AppWizard
October 16, 2026

Googlebook review: Android on a laptop is still Android

Setting up a Googlebook for Android users involves scanning a QR code to transfer accounts, data, and applications, requiring Android 17 for optimal integration. Google’s “Better Together” services allow access to files, synchronization of notifications, and app mirroring from an Android 17 phone. Both devices must be on the same Wi-Fi network for connectivity, and users may face limitations such as performance issues, incompatibility with system-level security apps, and the restriction of one app at a time. File access from the phone to the Googlebook is slow and one-way, with the Google Files app on the phone unable to access the Googlebook. The Files app on the Googlebook lacks features like tab support and network share compatibility, making the experience feel limited compared to traditional file management systems.
Ledger Atom puts everyday Android apps behind a hardware security layer
AppWizard
October 15, 2026

Ledger Atom puts everyday Android apps behind a hardware security layer

Ledger has introduced the Ledger Atom, an Android device designed to enhance the security of crypto transactions, AI actions, and private communications, priced at USD 9 and expected to launch in summer 2027. It functions as a security-centric companion rather than a smartphone replacement, combining Android with Ledger OS and a secure element chip. The device features a mode switch between Standard Mode and Secure Mode, with operations in Secure Mode isolated from Android. Ledger Atom will support physical approval for AI agent actions, requiring user consent on the device before proceeding. It will also serve as the interface and signer for Ledger Wallet, allowing users to manage crypto transactions securely. The device supports GPG/OpenPGP encryption for messaging and includes a physical privacy switch to disable cameras and microphones. Ledger Atom is currently available for reservation in a limited Founder’s Edition, requiring a refundable deposit, and includes a Bitcoin voucher and three months of Ledger Recover upon launch. Delivery will depend on product certifications, including FCC approval.
Google’s new Googlebook has clever AI tricks. I’d still pick a Windows laptop
Winsage
October 15, 2026

Google’s new Googlebook has clever AI tricks. I’d still pick a Windows laptop

Two new platforms have launched on the PC scene: the Googlebook and the Nvidia RTX Spark platform. The Acer Googlebook 14 was reviewed by Ashley Biancuzzo, while the reviewer is currently focusing on Lenovo’s Googlebook 15, which has a subpar keyboard but features Google’s new Aluminium OS aimed at enhancing the Chromebook experience with AI-powered productivity. To fully utilize the Googlebook, an Android phone running Android 17 is required, although some Samsung phones have been allowed to connect. In contrast, Windows offers Phone Link, which connects an Android phone to a Windows PC and only requires Android 10, allowing for photo transfers, calls, messages, and running Android apps within PC windows. Phone Link is seen as a strong competitor to Googlebook’s offerings, except for app streaming.
silver Android smartphone
AppWizard
October 13, 2026

5 Android Apps to Declutter & Secure Your Phone

Taps, swipes, and endless scrolling characterize the smartphone experience, often overwhelming users with notifications and personal data exposure. Innovative Android utilities are available to help users organize their digital environment and enhance privacy. 1. DBMB (Unknown Call Silencer): Silences unknown calls while keeping them logged. Operates offline for enhanced privacy and allows exceptions for trusted contacts in the Pro version. 2. Cork (Website/App Organizer): Creates a personalized, tile-based dashboard for frequently visited sites and essential applications. Users can customize tiles and pin them to the home screen for easy access. 3. Hidebox (Privacy Vault): Provides an encrypted vault for sensitive files, secured by PIN, fingerprint, or face-unlock. Features include a disguised app icon, a decoy vault, intruder selfies, and encrypted Google Drive backups. 4. Infinite Walls (Wallpaper App): Offers a vast catalog of curated 4K artwork and AI-generated wallpapers. Users can explore various categories and automate wallpaper changes with Pro features. 5. Floatkit (Floating Sidebar): Provides a floating sidebar for quick access to essential tools without leaving the current app. Includes features like global search, quick notes, and controls for volume and brightness.
silver Android smartphone
AppWizard
October 12, 2026

5 Android Apps to Declutter & Secure Your Phone

DBMB is an app that silences unknown calls while keeping a log of all calls, operating offline without relying on online databases. Cork organizes links and apps into visual boards, allowing users to create personalized dashboards for easy access. Hidebox provides an encrypted vault for sensitive files, secured by PIN or biometric access, with features like a disguised app icon and intruder selfies. Infinite Walls offers curated 4K artwork and AI-generated wallpapers for phone backgrounds, with options for automated changes. Floatkit provides a floating sidebar for quick access to essential tools and functions without leaving the current app, facilitating seamless multitasking.
A practical guide to cost optimization with Lakebase Postgres
Tech Optimizer
October 11, 2026

A practical guide to cost optimization with Lakebase Postgres

Lakebase is a fully managed Postgres database designed for modern application development, featuring an architecture that separates storage and compute with a serverless compute layer. This design allows for cost efficiencies through various mechanisms: 1. **Branching**: Developers can create isolated environments for development, testing, or experimentation without duplicating storage costs, as branches share the same underlying storage. 2. **Autoscaling**: Lakebase adjusts compute resources based on activity levels, allowing users to pay only for the compute they use. It can scale down during low activity and can be suspended entirely after inactivity, reducing costs to zero. 3. **Read Replicas and High Availability**: The separation of storage and compute allows for adding read replicas and high availability without incurring additional storage costs, as these instances utilize the same storage layer. 4. **Synced Tables**: Integration with the Databricks Intelligence Platform enables efficient data syncing, allowing users to sync only the necessary working set of data, which helps avoid unnecessary storage and sync costs. 5. **Sync Modes**: There are three sync modes (Snapshot, Triggered, Continuous) for transferring data from the Lakehouse to Lakebase, each with different cost implications based on data freshness requirements. 6. **Right-sizing Compute**: Users can set the initial compute range during project provisioning to avoid over-provisioning and unnecessary costs. 7. **Monitoring and Metrics**: The Lakebase Metrics dashboard provides insights into working set size and cache utilization, helping users optimize their compute sizing and performance. 8. **Point-in-Time Restore (PITR) and Snapshots**: PITR maintains history for recovery within a configurable window, while snapshots offer discrete recovery points. Both are priced lower than standard storage, making them cost-effective options for data recovery. Lakebase costs are categorized into compute, storage, and serverless pipeline compute for syncing data. Compute is measured by CU usage, while storage includes branch storage, PITR history, and snapshot storage, all tracked separately. Users can access detailed usage and cost information through system billing tables.
Amazon Aurora PostgreSQL now supports direct querying of Apache Iceberg and Parquet data in your data lake
Tech Optimizer
October 11, 2026

Amazon Aurora PostgreSQL now supports direct querying of Apache Iceberg and Parquet data in your data lake

Amazon has introduced a new capability for Amazon Aurora PostgreSQL that allows users to query operational data alongside data stored in data lakes formatted in Apache Iceberg and Apache Parquet. This feature enables direct access to Iceberg REST Catalog-compatible catalogs, eliminating the need for data duplication or relocation. The integration of DuckDB within Aurora PostgreSQL allows users to query live operational data, including uncommitted writes, alongside data from data lakes using standard PostgreSQL syntax. This capability is available on Aurora PostgreSQL versions 17 (starting with 17.11) and 18 (starting with 18.6). Users must create an Aurora PostgreSQL cluster, attach an IAM role with the AuroraAnalytics feature, and enable the aurora_analytics extension to utilize this feature. They can create foreign tables referencing Iceberg or Parquet data in the data lake, and query them using familiar PostgreSQL commands. Aurora optimizes query performance through techniques like predicate pushdown and column pruning, and users can monitor query behavior with metrics provided by aurora_analytics_stat_statements(). Direct querying of Apache Iceberg and Parquet data is available across all commercial AWS Regions and AWS GovCloud (US) Regions without additional charges, aside from incremental Aurora compute and Amazon S3 request costs.
AWS embeds DuckDB in its PostgreSQL DBMS to speed queries of live and historical data
Tech Optimizer
October 10, 2026

AWS embeds DuckDB in its PostgreSQL DBMS to speed queries of live and historical data

Amazon Web Services Inc. has enhanced its Aurora PostgreSQL database management system to allow users to query the Apache Iceberg data lake directly. This feature integrates the DuckDB analytical engine, enabling seamless access to live transactions and historical records without data duplication or complex ETL processes. Customers can use existing PostgreSQL applications to query data in Amazon S3, including S3 Tables. The integration aims to reduce the engineering workload associated with data pipelines and supports real-time applications. DuckDB processes analytical scans within Aurora, eliminating extra network hops and allowing single queries to access both live and archived data. The feature supports external catalogs compliant with the Iceberg REST Catalog specification and can create foreign tables referencing data across multiple catalogs. Aurora optimizes query performance by filtering records and caching frequently accessed data. Customers can combine recent transactions in Aurora with historical data from S3 without manual schema definitions. For low-latency workloads, selected data can be copied into native Aurora tables using standard SQL. This capability requires the aurora_analytics extension and an AWS IAM role for S3 and Glue access, and is compatible with Aurora PostgreSQL versions 17.11 and 18.6. The feature is available across all AWS regions at no additional charge, with costs incurred only for Aurora computing resources and S3 requests.
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