All news with #cloud sql tag

🔁 This article explains how Google Cloud's Database Migration Service (DMS) automates translating SQL Server stored procedures that return multiple result sets into PostgreSQL equivalents. It outlines the decision matrix that maps simple single-result procedures to PROCEDURE objects and complex multi-result or mixed-return routines to FUNCTIONs returning SETOF refcursor, and describes the testing and application integration changes required.

🔍 At Google Cloud Next, Google announced the preview of graph algorithms in Spanner Graph, bringing Google Research’s graph mining capabilities natively to Spanner to deliver faster, cost-effective, large-scale structural analytics. The feature integrates with ISO GQL, runs on dedicated compute to avoid transactional impact, and scales to graphs with tens of billions of edges. Results can be written back to Spanner or exported to Cloud Storage.

🚀 AlloyDB for PostgreSQL introduces a Hot Standby HA architecture that keeps the standby node actively replaying WAL records, reducing failover time and preserving cache warmth. This change eliminates standby database startup delays and minimizes post-failover performance degradation, improving RTO and stabilizing application throughput. Hot Standby is rolling out for PostgreSQL 18 and will reach earlier versions in months, with no extra cost and retention of the 99.99% SLA.

🛠️ At Google I/O 2026, Google announced expanded integration between AI Studio and Google Cloud, allowing new users to deploy up to two full-stack apps on the Starter Tier without a billing account. Developers can now choose between Firestore (non-relational) and Cloud SQL (relational) with Firebase Auth for unified authentication. The AI agent can infer or provision the appropriate database, provision resources, generate schema and code, and deploy apps directly to Cloud Run for rapid prototyping.

🚀Urban Outfitters, Inc. (URBN) recently migrated its IBM Sterling OMS from an 11TB Oracle backend to Google Cloud’s AlloyDB for PostgreSQL to reduce TCO and improve scalability and performance. The migration was executed through close collaboration among URBN, IBM, and Google Cloud, with embedded engineering teams driving planning, testing, and tuning. Outcomes included optimized storage and compute, two read replicas for higher availability, significant performance improvements, and a shift toward open standards to future-proof operations.

🔍 QueryData launches in preview, offering near-100% accuracy translating natural language into database queries across AlloyDB, Cloud SQL (MySQL and PostgreSQL) and Spanner. Built on Google Cloud’s Gemini LLM and augmented by rich database context, it uses schema ontologies, query blueprints and ambiguity detection to generate precise queries. Deterministic security is enforced via Parameterized Secure Views (PSVs), and integration is supported through a unified QueryData API, the MCP Toolbox for Databases, and context-engineering tools including an Evalbench framework.

🔒 ID.me moved its identity platform to Google Cloud to handle massive scale and improve AI-driven fraud detection. The team migrated over 50 TB across 15 database instances and adopted a two-tier architecture using AlloyDB for heavy workloads and Cloud SQL for standard services. This reduced provisioning and maintenance overhead, sped development from weeks to days, and lowered data-team work time by 40% while enabling real-time fraud analysis.

🚀 Manhattan Associates modernized its Manhattan Active SaaS platform by migrating from legacy Oracle and DB2 to Google Cloud databases. Cloud SQL and BigQuery now power core transactions and real-time analytics, enabling over a billion API calls per day with average responses under 150 ms. Containerized microservices on GKE, Pub/Sub streaming, and managed observability deliver automated failover, cross-region recovery, and faster feature delivery. The shift reduced manual scaling and licensing overhead while boosting operational agility and resilience.

🚀 Cloud SQL now supports autoscaling for read pools in MySQL and PostgreSQL, enabling dynamic adjustment of read-replica capacity based on CPU utilization or average database connections. Read pools present a single stable read endpoint for 1–20 nodes, simplifying application configuration during traffic spikes. Autoscaling is generally available with the Enterprise Plus edition and helps reduce operational overhead, optimize costs by scaling in during low demand, and maintain high availability.

🚀 In 2025, Spanner became a first-class database for AI and multi-model workloads, integrating vectors, graphs, and text search to provide richer context for generative applications. Google expanded AI integrations including ML.PREDICT, Vertex RAG Engine support, an Agent Development Kit, and ANN search with ScaNN to speed semantic retrieval. The release also bridged operational and analytical silos with a columnar engine and tighter BigQuery/Iceberg integrations, simplified Cassandra and MySQL migrations, boosted price-performance, and strengthened enterprise safeguards such as drop protection and default backup schedules.

🔌 AlloyDB now offers managed connection pooling for PostgreSQL as a generally available capability, reducing connection overhead and improving scalability. The service-managed pooler listens on port 6432 and reuses backend connections to cut latency and resource churn, while Google Cloud handles setup, configuration, and maintenance. Choose Transaction or Session pooling based on compatibility needs and configure sizes via Console, gcloud, or API. Customers report support for 3x more clients and up to 5x higher transactional throughput.

⚡ Cloud SQL for MySQL Enterprise Plus now includes optimized writes, an automated runtime tuning suite that adjusts MySQL configuration and I/O behavior to reduce write latency and increase throughput. Enabled by default on Enterprise Plus instances, the feature implements adaptive purge, adaptive I/O limits, sharded I/O, faster REDO recovery, and adaptive buffer-pool warmup. Google provides a reproducible sysbench benchmark and reports up to 3x write throughput improvements versus the Enterprise edition, with results varying by machine type and workload.

📍 Oracle Database@AWS is now generally available in US‑East‑2 (Ohio), EU‑Central‑1 (Frankfurt), and AP‑Northeast‑1 (Tokyo). With this expansion, customers can run OCI Exadata Database Service, OCI Autonomous Database on Dedicated Infrastructure, and OCI Autonomous Recovery Service within AWS data centers across five regions. The launch simplifies migration of on‑premises Exadata workloads and helps meet in‑region data residency requirements. To consume the services, customers request a private offer from Oracle via the AWS Marketplace and provision resources through the AWS Management Console.

🚀 CME Group partnered with Google Cloud to migrate its critical trading databases to Cloud SQL, aiming to sustain ultra-low-latency operations and reduce operational overhead. The managed service provides built-in observability and AI-assisted insights that surface anomalies and suggest query optimizations, enabling teams to identify root causes in minutes. As a result, administrators focus on strategic improvements while developers iterate faster and collaborate across environments.

🚀 Google Cloud today announced a 30-day free trial for Cloud SQL, offering preconfigured MySQL and PostgreSQL instances to evaluate enterprise-grade features without upfront commitment. The trial exposes Performance, High Availability, and Data Cache capabilities and mirrors production-oriented SKUs (Enterprise and Enterprise Plus). Users can one-click upgrade to paid instances at any time; after 30 days instances are suspended and kept stopped for an additional 90 days at no charge. The offer is available in all Google Cloud regions.

☁️ Global Payments partnered with Google Cloud to design a multi-region, highly available database architecture using Cloud SQL Enterprise Plus. The deployment spans three regions with zonal replication, read replicas, cascading replication, and Cloud SQL Auth Proxy integration to support low-latency reads and rapid failover. This configuration yields near-zero planned downtime, sub-minute RTO and zero RPO for Tier 1 workloads, while meeting PCI DSS, GDPR, and NIST requirements.

🚀 Giles AI migrated its healthcare-focused platform to Google Cloud to reduce latency, improve scalability, and accelerate developer velocity. Using Google Kubernetes Engine, Cloud Run, and Compute Engine, the company orchestrates complex clinical data flows and routes prompts through Vertex AI and Model Garden to remain model-agnostic. Data storage and extraction are handled with Cloud SQL, Cloud Storage, and Document AI, while Cloud Armor and Security Command Center bolster security and compliance. Early customer results include dramatic reductions in research time and improvements in response accuracy.

🚀 Google has made Axion-powered C4A and Intel-based N4 virtual machines generally available for Cloud SQL Enterprise Plus and Enterprise editions, promising substantial gains in throughput and price-performance. Hyperdisk Balanced storage is supported on both families to boost I/O, increase throughput, and allow independent configuration of capacity, throughput, and IOPS. Customer tests report lower costs, reduced latency, and large throughput gains. These machines are available in select regions; check Cloud SQL pricing and region documentation for details.

🔧 Google released open-source Gemini CLI extensions that integrate Gemini with Google Data Cloud services, enabling terminal-based access to BigQuery, Cloud SQL, and AlloyDB. Developers install the CLI (recommended v0.6.0), add extensions, and configure IAM and environment variables to connect to projects. Extensions support provisioning databases and users, natural-language querying, AI forecasting, and conversational analytics, though some require enabling additional APIs.

🛠️ Gemini Cloud Assist Investigations is now in public preview to help troubleshoot Dataproc and Serverless for Apache Spark workloads by automatically analyzing driver and executor logs, Spark UI metrics, configurations, and cross-product telemetry. Accessible from the Google Cloud console and via API, it produces prioritized summaries and clear remediation steps. The tool is tailored to data engineers, data scientists, SREs, and managers to reduce investigation time and accelerate fixes.