Automobilbranche: Mercedes erwägt Einstieg in Rüstungsproduktion
Mercedes-Benz zieht eine Produktion von Militärgütern in Erwägung. Das Geschäft müsse aber wirtschaftlich sinnvoll sein. (Mercedes Benz, Wirtschaft)
Quelle: Golem
Mercedes-Benz zieht eine Produktion von Militärgütern in Erwägung. Das Geschäft müsse aber wirtschaftlich sinnvoll sein. (Mercedes Benz, Wirtschaft)
Quelle: Golem
Eine Canva-Studie zeigt: Marketing-Profis erhöhen die KI-Budgets für 2026, obwohl Verbraucher die Inhalte oft ablehnen. (Studien, KI)
Quelle: Golem
Das US-Militär hat erstmals einen bewaffneten, vierbeinigen Roboter für operative Tests durch ein Spezialkräftekommando freigegeben. (Militär, Roboter)
Quelle: Golem
Einige chinesische Autohersteller haben eine absurde Fahrwerksfunktion entwickelt: Der SUV hebt ein einzelnes Rad in die Luft und fährt weiter. (Auto, Mobilität)
Quelle: Golem
Die nuklear angetriebenen Schlachtschiffe der Trump-Klasse sollen die Machtverhältnisse auf den Weltmeeren neu ordnen. (Militär, Politik)
Quelle: Golem
PostgreSQL has become foundational to how modern applications are built. It powers everything from early‑stage startups to some of the most demanding production systems in the world. Its longevity isn’t accidental, it’s the result of decades of engineering discipline, community collaboration, and a relentless focus on correctness and extensibility.
As application architectures evolve, and as AI becomes a default part of the software stack, PostgreSQL continues to adapt. This adaptability is a key reason Microsoft has been investing deeply in PostgreSQL: 345 commits contributed to the latest PostgreSQL release, a team of PostgreSQL committers and contributors working directly on the upstream project, and a growing portfolio of managed services, developer tools, and community programs built around Postgres on Azure. Here’s what’s driving that investment, and what it means for the people building on Postgres today.
Figure 1: This infographic highlights the many ways Microsoft contributes to and supports the PostgreSQL ecosystem
Discover Azure HorizonDB
Why PostgreSQL, and why now
Across industries, PostgreSQL is increasingly the default choice for new workloads and modernization projects. That shift is driven by three clear trends.
PostgreSQL is trusted with real production systems
PostgreSQL earned its reputation by solving hard problems in production environments: transactional correctness, concurrency control, extensibility, and operational resilience. These characteristics weren’t designed for isolated benchmarks; they emerged through years of running mission critical systems under real pressure.
Microsoft runs PostgreSQL at global scale and sees these same patterns firsthand. Many upstream contributions, such as recent work in PostgreSQL 18 on asynchronous I/O, vacuum behavior, and query planning, are informed directly by production bottlenecks encountered at scale.
This feedback loop works both ways. Improvements made upstream benefit the entire PostgreSQL ecosystem, while lessons learned from large‑scale deployments continue to inform future development.
Databases are becoming part of the AI stack
Databases are no longer isolated storage layers. In modern systems, they increasingly sit inside feedback loops that involve reasoning, ranking, and decision‑making.
Developers building AI‑enabled applications are asking new questions:
How close can vector data live to transactional data?
How can similarity search respect SQL predicates?
How can inference, ranking, and structured data work together without excessive glue code?
PostgreSQL’s extensibility makes it a natural foundation for these patterns. That’s why Azure Database for PostgreSQL and Azure HorizonDB focus on integrating AI‑related capabilities, such as vector search and model invocation, directly into familiar PostgreSQL workflows.
Different workloads, different paths to scale
As applications scale, not every workload benefits from the same architectural approach.
Some teams want a fully open, single‑node PostgreSQL experience with minimal abstraction. Others need elastic scale, multi‑zone replication, and fast failover but don’t want to push complexity into the application layer.
This diversity is why Microsoft supports multiple PostgreSQL deployment models on Azure:
Azure Database for PostgreSQL for open‑source‑aligned workloads and lift‑and‑shift scenarios.
Azure HorizonDB for cloud‑native systems that require scale‑out compute, shared storage, and low‑latency global resilience.
These aren’t forks. They are different engineering responses to different workload realities.
Get started with Azure Database for PostgreSQL
Upstream collaboration and developer tooling
Microsoft’s investment in PostgreSQL goes beyond product announcements for Azure’s managed services to include shipped code from in-house contributors, upstream collaboration, and production reliability. As our learnings expand, we’ve used these insights to enrich the open-source Postgres engine for the broader community.
Upstream contributions that benefit everyone
Postgres committers and developers at Microsoft actively contribute to the PostgreSQL open source project, working alongside the global community on core improvements. Recent version updates include contributions across:
Asynchronous I/O foundations.
Performance improvements in vacuum and memory management.
Planner and execution enhancements for large datasets.
These changes land upstream first, ensuring that improvements are broadly available not tied to any single cloud or service. A transparent overview of our Postgres work is published annually.
Architectural motivations behind Azure HorizonDB
Azure HorizonDB was built to address a specific class of PostgreSQL workloads that are constrained by single node scaling but not well served by application level sharding. For example, high-throughput, low-latency systems that require horizontal scale without adding application complexity.
Key architectural goals shaped Azure HorizonDB:
Independent scaling of compute and storage.
Failover and recovery operations decoupled from data size.
Multi‑zone replication enabled by default.
The result is a PostgreSQL‑compatible service with a shared‑storage, scale‑out design supporting sub‑millisecond multi‑zone commits and growth to thousands of cores, without requiring application rewrites.
Azure HorizonDB extends PostgreSQL’s reach while maintaining compatibility expectations that developers rely on.
Improving the developer experience where work actually happens
PostgreSQL has long been a developer‑centric database. Tooling investments on Azure reflect that mindset.
With more than 500,000 installs, the Visual Studio Code extension for PostgreSQL brings provisioning, schema exploration, performance diagnostics, and migration workflows directly into the IDE developers already use. Integrated GitHub Copilot assistance helps with SQL authoring, tuning, and even complex migrations, such as Oracle to PostgreSQL, which is one of the most challenging real world scenarios teams face.
The extension helps to remove unnecessary friction while keeping PostgreSQL familiar.
Investing in the PostgreSQL ecosystem
PostgreSQL’s progress has always depended on its community. That’s why Microsoft’s investment extends beyond products and services.
Microsoft sponsors and helps organize PostgreSQL conferences and user groups worldwide including PGConf.dev, PGConf EU, PGConf India, and many others. POSETTE: An Event for Postgres is a free and virtual Postgres event organized by the Postgres team at Microsoft and in partnership with AMD. It covers a wide range of topics including internals, ecosystem tools, real world debugging stories, and production architectures. This year’s 5th annual event, hosted 16-19 of June, brings together contributors, users, and engineers from across the Postgres community to share what works in practice.
Explore the schedule for POSETTE 2026
Talking Postgres, a monthly podcast that our team produces, features conversations with people who work with Postgres, from longtime contributors to production engineers solving hard problems at scale.
And the Microsoft Blog for PostgreSQL provides regular deep dives on product updates, migration guidance, and real-world Postgres usage patterns on Azure.
Looking ahead
PostgreSQL is approaching its fourth decade and it’s still accelerating. What began as a research project at UC Berkeley, is now a widely used database for modern applications, from developer experiments to mission-critical production environments.
As the community celebrates this moment, Microsoft’s focus remains consistent:
Strengthening PostgreSQL core through upstream collaboration.
Extending PostgreSQL responsibly for AI‑driven and cloud‑native workloads.
Preserving developer trust through open standards and transparency.
These priorities shape ongoing investments in Azure Database for PostgreSQL, Azure HorizonDB, developer tooling, and community engagement. Updates across these areas are now shared regularly through the Microsoft for PostgreSQL LinkedIn page.
A clear takeaway
PostgreSQL’s success has always been rooted in engineering discipline and community trust. Sustaining that success requires meaningful, long‑term investment, not just in services, but in the project itself and the people behind it.
Microsoft’s commitment to PostgreSQL reflects that belief: contributing upstream, building thoughtfully, and supporting an ecosystem that continues to move the database forward.
Unlock AI‑Ready Performance with Azure Database for PostgreSQL
Build intelligent, high‑performance apps with a fully managed PostgreSQL service that scales effortlessly.
Try today!
The post From commit to cloud: Powering what’s next for PostgreSQL appeared first on Microsoft Azure Blog.
Quelle: Azure
Today, AWS announces that the AWS Partner Central agents now accelerate opportunity creation through natural language conversation. AWS Partner Central agents, released on March 16, 2026, are AI-powered capabilities built on Amazon Bedrock AgentCore that help partners surface pipeline insights, advance deals with next-step recommendations, and identify funding opportunities. With this update, partners create opportunities through a short conversation instead of completing a multi-step form, so partner sales teams spend less time on data entry and more time selling. Partners describe a deal in natural language, upload meeting notes, proposals, or call transcripts (PDF, DOCX, Excel, TXT), or clone an existing opportunity. The agent extracts the information, enriches customer details, and recommends improvements — such as adding missing context, correcting field values, or strengthening the business problem statement — so partners submit higher-quality opportunities, improve pipeline hygiene, and shorten sales cycles. Partners use the feature in the AWS Console through Amazon Q chat, and programmatically through Model Context Protocol (MCP), so sales teams create opportunities from their existing tools. AWS Partner Central agents are available in all commercial AWS Regions. To learn more about agentic capabilities in AWS Partner Central, review this blog. Partners can start using agents by visiting AWS Partner Central in the AWS console and accessing opportunities, after reviewing the agents guide, and to integrate agents into your existing tools, visit the Partner Central agents MCP server guide.
Quelle: aws.amazon.com
Amazon EMR Serverless is now generally available in six additional AWS Regions – Asia Pacific (Hyderabad), Asia Pacific (Malaysia), Asia Pacific (New Zealand), Asia Pacific (Taipei), Asia Pacific (Thailand), and Mexico (Central). Amazon EMR Serverless is a deployment option in Amazon EMR that makes it simple and cost effective for data engineers and analysts to run petabyte-scale data analytics in the cloud. With EMR Serverless, you can run your Apache Spark and Apache Hive applications without having to configure, optimize, tune, or manage clusters. EMR Serverless offers fine-grained automatic scaling, fast launch times, customizable worker configurations, and support for batch, interactive and streaming workloads. To get started, visit the Amazon EMR Serverless User Guide. For pricing info, visit the EMR Serverless pricing page.
Quelle: aws.amazon.com
Amazon CloudWatch Logs now supports retrieving up to 100,000 results using the Logs Insights query language. Customers can specify the limit in their query using the LIMIT command. Previously, customers were limited to 10,000 results and had to split their queries into smaller time ranges to retrieve all results. With this launch, customers can view a larger set of results and use existing features such as patterns, visualization, and export on the full 100,000 result set. The GetQueryResults API has also been updated to support pagination; each invocation can return up to 10,000 results along with a token that can be used to fetch the next set of results. The increased query result limits are available in all commercial AWS regions. You can execute queries and view up to 100,000 results using the Amazon CloudWatch console, AWS CLI, AWS CDK, and AWS SDKs. To learn more, see the Amazon CloudWatch Logs documentation.
Quelle: aws.amazon.com
Die Minidisc kam eigentlich zur rechten Zeit. Doch mit einer seltsamen Produktstrategie verpasste Sony jede Chance. Von Christian Rentrop (MD, Sony)
Quelle: Golem