real-time analytics Archives

Tech Optimizer

March 17, 2026

How PostgreSQL on Azure helps modernize legacy databases

Microsoft is enhancing PostgreSQL to establish it as a high-performance, scalable, and enterprise-ready open database platform, addressing the limitations of legacy systems like Oracle. Many Oracle customers face rising licensing costs, performance bottlenecks, and scalability issues, prompting them to consider migration. Apollo Hospitals successfully migrated from Oracle to Azure Database for PostgreSQL, achieving a 60% reduction in operational costs and a threefold improvement in system performance. Microsoft has introduced an AI-assisted migration tool to simplify the transition from Oracle to PostgreSQL, automating the conversion of schemas and application code. Azure Database for PostgreSQL offers high performance, scalability, and security, with features like v6-series compute SKUs and SSD v2 storage. Azure HorizonDB, a new cloud-native PostgreSQL service, supports extreme performance demands and is designed for real-time analytics. Microsoft is committed to enhancing PostgreSQL as an open-source database for enterprise workloads, enabling organizations to innovate and become more agile.

Tech Optimizer

March 17, 2026

EDB Accelerates Postgres for the Agentic Workforce Era with NVIDIA AI Infrastructure and Interactive Analytics

EnterpriseDB (EDB) has advanced its integration with NVIDIA's cuDF for Apache Spark to enhance Postgres® performance on NVIDIA AI infrastructure, achieving analytics capabilities up to 100 times faster than traditional methods. EDB emphasizes the need for a real-time analytics framework to address challenges posed by fragmented data silos and inefficient analytics processes. Key features of EDB Postgres AI include GPU-acceleration for interactive analytics, NVIDIA NIM model serving, fully air-gapped support for private registries, and high-speed retrieval with NVIDIA NeMo Retriever. Research indicates only 13% of enterprises have transitioned to production-scale agentic deployments, which report five times higher ROI. The EDB PG AI Analytics Engine can achieve 50–100x faster analytics on large datasets, supports lakehouse architectures, and ensures workload isolation and governance. EDB PG AI is positioned as a secure, compliant, and scalable platform for operationalizing data and AI workloads.

Tech Optimizer

March 12, 2026

Why Postgres® has won as the de facto database: Today and for the agentic future

The AI economy is projected to reach a trillion by 2028, leading 95% of major global enterprises to establish AI and data platforms within two years, although only 13% have succeeded so far. Successful integration of agentic AI requires moving away from outdated architectures to a cohesive data and AI approach. Currently, 81% of successful enterprises utilize open-source strategies, with over 40% standardizing on PostgreSQL. PostgreSQL's extensibility allows for the integration of diverse data types, essential for AI applications. It provides a unified database engine that mitigates issues associated with fragmented architectures. PostgreSQL benefits from a large independent developer community, which enhances its innovation and adaptability. To thrive in the future, organizations must abandon legacy systems and leverage PostgreSQL's capabilities for a sovereign data platform.

Tech Optimizer

February 14, 2026

Snowflake makes enterprise data AI-ready with native Postgres in its AI Data Cloud

Snowflake has introduced advancements to make data ready for artificial intelligence (AI) by integrating enhanced interoperability, governance, and resilience features into its platform. The latest version of Snowflake Postgres operates natively within the AI Data Cloud, allowing businesses to unify transactional, analytical, and AI functions on a single platform. This integration helps dismantle data silos and fragile pipelines, facilitating real-time analytics and AI capabilities without complex data pipelines. Snowflake Postgres is fully compatible with open-source Postgres, enabling companies to migrate existing applications without code modifications. It allows enterprises to directly query and manage Apache Iceberg tables using standard SQL, minimizing data movement and simplifying architectures. Snowflake also enhances data governance and collaboration across various formats, ensuring AI systems can scale effectively. Additionally, Snowflake's data protection measures, including backups, bolster resilience against disruptions.

Tech Optimizer

February 14, 2026

PostgreSQL vs MySQL: Which Database is Better in 2026?

PostgreSQL 17 introduces significant enhancements, including refined memory management in VACUUM processes, improved SQL/JSON capabilities with features like JSON_TABLE(), advancements in logical replication and parallel processing, and overall increased efficiency for handling complex queries and large datasets. MySQL, under Oracle's stewardship, focuses on performance, reliability, and cloud integration, with updates unveiled at the HeatWave Summit in 2025 that support both transactional and analytical workloads in a unified system, enabling real-time analytics without data transfer to separate tools.

Tech Optimizer

February 12, 2026

Snowflake unveils Postgres to make enterprise data AI-ready

Snowflake has introduced Snowflake Postgres, which will be generally available soon, designed to unify transactional workloads, analytics, and AI development within its AI Data Cloud. It is fully compatible with open-source Postgres, allowing for seamless migration of existing applications without code modifications. Snowflake Postgres integrates Apache Iceberg through pg_lake, enabling users to manage Iceberg tables using standard SQL, reducing data movement between systems. Companies like BlueCloud and Sigma Computing have adopted it for operational applications and real-time analytics. Alongside Snowflake Postgres, Snowflake has enhanced data governance and interoperability through the Snowflake Horizon Catalog, which allows for better access and governance across various systems. The Horizon Catalog supports querying Iceberg tables and managing data stored in them. Snowflake has also launched Open Format Data Sharing, extending its zero-ETL sharing model to open formats like Apache Iceberg and Delta Lake, and has integrated with Microsoft OneLake for secure data sharing. Additionally, Snowflake has made Snowflake Backups generally available to safeguard business-critical data and ensure compliance with regulatory requirements, allowing for quicker recovery from disruptions.

Tech Optimizer

February 12, 2026

Databricks launches PostgreSQL Lakebase to aid AI developers

Databricks Lakebase has transitioned to general availability, launched on AWS on February 3, following the acquisition of Neon for billion in May 2025. Lakebase is a PostgreSQL database designed for AI development, integrating with Databricks' Data Intelligence Platform to provide an operational database alongside data lakehouse capabilities. It decouples compute from storage to improve resource management and includes autoscaling features to manage costs. Lakebase also offers unified governance through Databricks' Unity Catalog. Analysts highlight its ability to reduce friction between operational and analytical data, enabling real-time applications with up-to-date governed data and minimizing extensive ETL processes. Key features include serverless autoscaling and instant database branching for enhanced developer productivity. Databricks aims to simplify database management at scale and demonstrate a lower total cost of ownership to compete with Snowflake.

Tech Optimizer

January 28, 2026

EDB Demonstrates Strong Global Momentum and Cross-Industry Adoption of EDB Postgres® AI

MNTN, Waystar, and NTT East have adopted EDB Postgres AI (EDB PG AI) to modernize their data platforms, enabling agentic AI, real-time analytics, and mission-critical operations while maintaining control over data and infrastructure. EDB's Sovereignty Matters research indicates that enterprises focusing on scalable agentic AI prioritize sovereign control of data, hybrid deployment flexibility, and a unified platform for transactions, analytics, and AI workloads. MNTN modernized its data warehouse for high-volume advertising data, Waystar consolidated its data infrastructure for healthcare transaction processing, and NTT East enhanced AI-driven network operations while ensuring data locality control. The adoption of EDB PG AI reflects a growing market demand for open-source database foundations, with 35% of enterprises considering PostgreSQL for complex workloads. EDB PG AI provides an open-source foundation, accelerated AI development, hybrid deployment flexibility, and enterprise-grade reliability.

Tech Optimizer

January 27, 2026

PostgreSQL for WMS: a DBMS selection strategy in the era of import substitution

Choosing a Database Management System (DBMS) for Warehouse Management Systems (WMS) is a strategic decision that impacts security, budget, and adaptability. PostgreSQL is identified as a safe, cost-effective, and future-proof solution for Russian warehouse systems, especially following the withdrawal of foreign vendors like Oracle and Microsoft SQL Server. Starting September 1, 2025, foreign software usage in government bodies and companies with over 50% state ownership will face legal restrictions, posing regulatory risks for those using Oracle. Financial risks include high licensing fees and the potential for legal prohibitions on current technologies. Business continuity risks arise from the possibility of vendors ceasing support and updates. PostgreSQL, both in its vanilla form and commercial derivatives like Postgres Pro, is presented as a robust alternative capable of handling high loads and providing necessary features for modern WMS. It supports real-time analytics and advanced capabilities such as intelligent search and automatic classification using neural networks. Key considerations when choosing a DBMS include estimating data volumes, checking legal requirements, and calculating total cost of ownership (TCO).

Tech Optimizer

December 24, 2025

Antivirus vs Endpoint Security in 2025: Which Protection Do You Really Need?

In 2025, users must choose between traditional antivirus software and modern endpoint security solutions for their digital safety. Antivirus software has evolved to include machine learning and cloud-based threat analysis, effectively combating various malware types but primarily protects individual devices. It is user-friendly and suitable for casual users but struggles against sophisticated attacks and lacks centralized management. Endpoint security, on the other hand, secures all network-connected devices and employs advanced technologies like AI-driven threat detection and real-time behavioral analytics. It offers proactive monitoring and automated threat responses, making it essential for businesses and professionals handling sensitive information. Endpoint security provides centralized management and a broader range of protections but is typically more expensive and may require technical expertise to set up. The choice between the two solutions depends on individual needs: casual users may prefer antivirus software, while professionals and businesses benefit from the comprehensive protection of endpoint security. As cyber threats become more complex, endpoint security is becoming the standard due to its proactive and automated defense capabilities.