data storage Archives

TrendTechie

July 24, 2026

BitTorrent исполнилось 25 лет. Как программа одного человека изменила интернет и поставила Голливуд в тупик

On July 2, 2001, Bram Cohen announced the operational status of his program, BitTorrent, on a mailing list for peer-to-peer network developers. BitTorrent revolutionized file sharing by segmenting files into smaller pieces, allowing users to download from multiple sources simultaneously and share already downloaded data, which improved download speeds as file popularity increased. Unlike earlier peer-to-peer networks, BitTorrent did not have a built-in catalog, relying on external websites for users to locate torrents. The first major torrent catalog, Suprnova, emerged in 2002, followed by The Pirate Bay in 2003, making the protocol widely accessible. By 2004, BitTorrent accounted for nearly a third of all internet traffic. In 2004, Cohen founded BitTorrent Inc., which acquired the client µTorrent in 2006. The company launched the BitTorrent Entertainment Network in 2007, but it closed in 2008 due to competition from free pirated content. BitTorrent Inc. later explored various technologies but struggled to establish a sustainable business model. The protocol evolved with decentralization features like the distributed hash table (DHT) and magnet links. In 2018, BitTorrent was acquired by the blockchain project TRON for an estimated 0 million. BitTorrent Inc. claims around 54 million active users per month, with additional users on independent clients. Despite a decline in torrent traffic from its peak, the network has been experiencing growth, attributed to rising streaming costs and fragmented content availability.

Tech Optimizer

July 21, 2026

I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer

The author transitioned from a data analyst role to a data engineer, creating a 12-month self-study roadmap focused on learning by building projects. The first project was a GitHub ETL pipeline, which evolved from a simple Python script to a more complex system using SQLite and GitHub Actions for automation. The author realized that the challenges of data engineering lay in system design and orchestration rather than just writing ETL logic. For the second project, the author built an automated RSS ingestion pipeline to explore engineering decisions in creating a reliable data pipeline. The project emphasized the importance of separating application responsibilities from orchestration tasks, leading to the use of Docker for consistent execution environments and Kestra for orchestration. The author validated each component of the project incrementally: first the Python ETL, then PostgreSQL, followed by Docker, and finally Kestra. This approach ensured that each layer functioned correctly before adding complexity. The final architecture included distinct responsibilities for each component: Python for data processing, PostgreSQL for data storage, Docker for execution, and Kestra for orchestration. The author learned that effective engineering involves considering system reliability, error handling, and observability, shifting the focus from merely writing code to designing entire systems. The experience transformed the author's mindset, emphasizing the importance of incremental building and the separation of execution and orchestration responsibilities.

Tech Optimizer

July 12, 2026

What Is Serverless PostgreSQL?

Serverless PostgreSQL is a fully managed cloud database model that separates compute and storage, allowing them to scale independently and automatically based on demand. It eliminates the need for manual infrastructure provisioning and capacity planning, charging only for active usage. Unlike traditional PostgreSQL setups, which require continuous resource allocation and manual scaling, serverless PostgreSQL provisions resources on demand and can scale down to zero during idle periods. Serverless PostgreSQL integrates with serverless compute platforms, enabling analytical queries to access the same data within a unified architecture. Key differences between traditional and serverless PostgreSQL include manual versus automatic provisioning and scaling, fixed versus usage-based billing, and high versus reduced operational overhead. Lakebase architecture is an emerging model that combines transactional databases with lakehouse foundations, allowing operational and analytical workloads to coexist on a single platform. This architecture minimizes data duplication and simplifies access, enhancing data management and analysis. Serverless PostgreSQL operates on a cloud-native architecture that enhances efficiency by allowing compute and storage to scale autonomously. It features scale-to-zero behavior, where compute resources are suspended when inactive and reactivated upon new queries. Major providers include Databricks Lakebase, Amazon Aurora Serverless v2, and Neon, each offering varying capabilities and integrations. Pricing for serverless PostgreSQL typically includes charges for compute resources, storage, and data transfer, with costs fluctuating based on workload activity. Cold start latency is a performance consideration, as reactivating compute resources can introduce delays. Strategies to mitigate this include keeping resources partially active or selecting providers with minimal cold start impacts. Serverless PostgreSQL is well-suited for OLTP workloads, while lakebase architecture is better for AI development, variable workloads, and environments requiring rapid iteration. Setting up serverless PostgreSQL involves choosing a provider, creating a database instance, and configuring access settings. It can also be used alongside serverless compute platforms for analytics, further extending its capabilities.

AppWizard

July 2, 2026

All Android users just got an important backup feature

Google is introducing a selective backup feature for Android users, allowing granular control over app data management. This update is initially rolling out to Pixel devices and users of Google Play Services version 26.24. Users can now selectively manage backups for each app, which helps conserve cloud storage space. The feature is available for those using Android 16 and Android 17, with other manufacturers expected to adopt it soon. Once activated, data is securely backed up to the cloud, but users should be aware that disabling backup for an app will permanently delete its previously backed-up data. To manage backups, users can go to their device’s settings under Google Services > Backup > Backup details. The rollout is gradual, primarily targeting Google Pixel smartphones. Most users will receive the update automatically, and they can check their version of Google Play Services in the settings.

Tech Optimizer

June 25, 2026

The database storage problem is solved. Here’s what comes next.

Postgres has been a reliable transactional database for three decades, used for managing customer records and financial transactions. Innovations in the Postgres ecosystem are now focused on minimizing data movement rather than just data storage. The challenge of interoperability is becoming crucial, as organizations seek to share operational data seamlessly across various systems without creating additional copies or pipelines. Many organizations are spending as much effort on data movement as on data storage. Postgres is increasingly viewed as the authoritative system for critical information, and its role is evolving to facilitate better interaction with operational data. Technologies like logical replication and change data capture are enhancing Postgres's integration within data ecosystems. The rise of AI has highlighted the need for real-time access to operational data and has prompted organizations to reconsider the necessity of maintaining multiple copies of the same data. The database industry is shifting focus from optimizing storage to enabling effortless data sharing across systems. Postgres continues to adapt to new workloads and architectural patterns, maintaining its reputation as a stable foundation for operational data while expanding its capabilities through innovative extensions.

Tech Optimizer

June 22, 2026

The database that refused to die: How Postgres survived its own creators

Postgres, originally developed by Michael Stonebraker in the early 1980s, is an open-source database system that evolved from Ingres. It was designed to handle complex data types and introduced user-defined data types, operators, and functions, leading to the support for abstract data types (ADTs). The initial commercialization of Postgres occurred through a startup named Illustra, later acquired by Informix. In 1995, graduate students Andrew Yu and Jolly Chen revived Postgres, transitioning it from QUEL to SQL, resulting in Postgre95, which evolved into PostgreSQL. Today, Postgres is one of the most popular database systems globally, known for its extensibility and high code quality. However, it currently lacks features like file-level encryption (TDE), which are standard in commercial systems, relying instead on the operating system for encryption. Efforts to implement TDE have faced challenges due to the complexity of required code changes.

AppWizard

June 21, 2026

The Useful Privacy Feature That Isn’t Enabled By Default On Your Android Phone

Private Space is a privacy feature available on Pixel and select Android devices, while Secure Folder is exclusive to Samsung devices. Both create a secure area within the smartphone for sensitive applications and data storage, operating independently from the primary user profile. Users can install apps and store files in these secure spaces without compromising their main profile's integrity. To activate Private Space, users navigate to Settings > Security and Privacy > Private Space, requiring a Google Account sign-in and a unique lock. For Samsung devices, the path is Settings > Security and Privacy > More Security Settings > Secure Folder, requiring a Samsung account. Private Space cannot be used on managed devices or with supervised accounts, and only the primary user can manage these secure areas. The Private Space or Secure Folder icon can be hidden for added security. The private area is distinctly separated from the core user profile, preventing open communication between the two spaces to safeguard against data harvesting. Android allows granular control over app permissions, and users are advised to isolate questionable apps within Private Space or Secure Folder to protect sensitive information.

Tech Optimizer

May 25, 2026

How to create a Metabase dashboard with Docker

Creating a self-hosted analytics dashboard using Metabase and Docker involves deploying the Metabase container, which integrates with PostgreSQL for data storage. The prerequisites include a server or local machine with Docker, terminal access, an available port (typically 3000), a PostgreSQL database, and connection details for the business database. The installation steps are as follows: 1. Pull the Metabase Docker image using `docker pull metabase/metabase:latest`. 2. Run the Metabase container with `docker run -d -p 3000:3000 --name metabase metabase/metabase`. 3. Verify the container operation using `docker ps` and check logs with `docker logs -f metabase`. 4. Access the Metabase setup wizard at `http://localhost:3000` or `http://your-server-ip:3000`. 5. Manage the Metabase container using `docker stop metabase`, `docker start metabase`, and `docker restart metabase`. For a production setup, it is recommended to integrate PostgreSQL for persistent storage. Steps include creating a project directory, a Docker Compose file, launching both Metabase and PostgreSQL containers, monitoring logs, accessing Metabase, managing the deployment with Docker Compose commands, and updating Metabase by pulling the latest image. To create a business intelligence dashboard, connect your business data source by selecting the database type and entering connection details. Create questions using the visual query builder or SQL, choose suitable visualizations, compile saved questions into dashboards, add filters for interactivity, and share the dashboard with stakeholders while managing permissions.

Tech Optimizer

May 22, 2026

AI Data Platform Modernization in Financial Services | Microsoft Azure PostgreSQL | The Microsoft Cloud Blog

Financial service institutions are increasingly exploring AI applications to alleviate operational burdens and gain a competitive edge, but face challenges with legacy data infrastructures that may not meet modern demands. The need for continuous availability and compliance is critical, as even brief downtime can have catastrophic consequences. Aging databases struggle with high-volume transactions and real-time analytics, prompting a focus on predictive maintenance and infrastructure automation. Microsoft Azure's PostgreSQL managed services, including Azure Database for PostgreSQL, address these challenges by providing flexible performance scaling and ensuring high availability. The service can trigger automatic failover within 60 to 120 seconds during outages, guaranteeing up to a 99.99% availability SLA. It supports read replicas for offloading analytics without impacting primary database performance and offers layered security controls, including encryption at rest and network isolation. Azure Database for PostgreSQL simplifies compliance with standards such as PCI DSS and SOC by enabling centralized identity and access management through Microsoft Entra ID authentication. It integrates seamlessly with the Microsoft ecosystem, allowing organizations to connect data to analytics and AI services without complex ETL processes. BNY Mellon successfully modernized its data platform by migrating to Azure Database for PostgreSQL in nine months, achieving improved resilience and allowing engineering teams to focus on innovation. The platform supports high availability, backup capabilities, and extensibility, empowering financial institutions to remain innovative in the era of AI.

Tech Optimizer

May 16, 2026

Chamber Perk: O’Brien Technologies Emphasizes Education and Protection

O’Brien Technologies has launched a program called “Educate and Protect” to improve cybersecurity for businesses by addressing the human factor in breaches. They highlight that many cyber threats arise from human errors, such as clicking phishing links or misunderstanding data storage protocols. The company points out that cloud services do not automatically protect files without robust backup systems and that small businesses are often more vulnerable due to a lack of comprehensive security measures. They stress the inadequacy of relying solely on outdated tools like firewalls and antivirus software and advocate for a multi-layered cybersecurity approach. O’Brien Technologies recommends regular employee training, staying informed about threats, and ongoing commitment to cybersecurity. They offer tailored guidance for businesses looking to enhance their cybersecurity. Interested parties can contact them at 661-432-1301 or visit obrienmsp.com.