Source URL: https://cloud.google.com/blog/products/databases/whats-new-for-google-cloud-databases/
Source: Cloud Blog
Title: Embracing gen AI with the latest Google Cloud databases innovations
Feedly Summary: Embracing gen AI means providing delightful AI-driven experiences to your users. As you take this journey, databases provide the foundation for building enterprise gen AI apps that are accurate, relevant and grounded in enterprise truth. At Google Cloud, we’re focused on helping you in three key ways.
First, helping developers build intelligent apps with operational data. Second, leveraging gen AI — and specifically our Gemini models — to simplify every stage of the database journey, including migrations, fleet management, troubleshooting, and performance optimization. And third, modernizing your databases so you can take advantage of gen AI. Let’s see how all three come to life.
Build enterprise gen AI apps with operational data
Developers play a key role in the success of gen AI in the enterprise. According to the Bureau of Labor Statistics, there are 10x more software developers compared to data scientists — an order of magnitude more technical practitioners who can innovate with AI. That’s why we’re excited about the innovations we’ve brought to developers over the past year: vector search, LangChain integration, and foundation models are supported across all our databases. We’ve also added powerful new features all in a single database, Spanner – the always-on, globally consistent, and virtually unlimited scale database. These features include graph processing, advanced full-text search, and vector search — — so you can build a new class of smart, contextually relevant applications that rely on interconnected data and semantic search.
We’ve also enhanced the gen AI capabilities in AlloyDB, the database that combines the best of Google with 100% PostgreSQL compatibility. Today, we’re announcing that the ScaNN vector index in AlloyDB is now generally available. This is the same technology that powers Google’s most popular services including Google Search and YouTube, infusing 12 years of research and innovation into AlloyDB. The ScaNN index is the first PostgreSQL-compatible index that can scale to support more than one billion vectors while maintaining state-of-the-art query performance — enabling high performance workloads for every enterprise.
We know that many organizations need the flexibility to deploy and run applications in various environments, and that’s why last year we launched AlloyDB Omni, a downloadable edition of AlloyDB that runs anywhere, including on-premises and on other clouds. However, customers have also asked us for a managed database service that runs across all major clouds.
Today, we’re announcing a strategic partnership with Aiven to help you deploy and manage AlloyDB Omni across any cloud. Aiven for AlloyDB Omni is a managed cloud database service that provides a simplified and secure way to deploy, manage, and scale AlloyDB Omni on Google Cloud, AWS, and Azure, improving multi-cloud operations. You can now run transactional, analytical, and vector workloads across clouds on a single platform, and easily get started building gen AI applications, also on any cloud. This is the first partnership that adds an administration and management layer for AlloyDB Omni. Learn more about Aiven for AlloyDB Omni.
Many gen AI applications benefit from an in-memory database that provides high throughput with low latency. And a community of contributors started working on a Redis fork called Valkey—a Linux Foundation project to provide a fully open source alternative to Redis. Last month, we announced Memorystore for Valkey 7.2, making Google Cloud the first major cloud provider to support it as a managed service. We’re also making ongoing investments in Memorystore, including vector search in the fully-managed Memorystore for Redis Cluster and Memorystore for Valkey 7.2 services.
A single Memorystore for Valkey or Memorystore for Redis Cluster instance can perform vector search at single-digit millisecond latency on over a billion vectors with greater than 99% recall. In addition, we’re announcing that Memorystore for Valkey 8.0 is now available in public preview. Valkey 8.0 includes major performance and reliability improvements, a new replication scheme, networking enhancements, and detailed visibility into performance and resource usage. Memorystore for Valkey 8.0 achieves up to 2x queries per seconds at microseconds latency when compared to Memorystore for Redis Cluster.
Switching gears, millions of developers use Google’s Firebase platform to build and run modern applications. Firebase developers have asked for expanded capabilities for building AI-powered experiences that users love. We’re excited to announce that Firebase Data Connect, Firebase’s first relational database solution, will be available in public preview later this month.
Firebase Data Connect is a new backend-as-a-service that is integrated with a fully managed PostgreSQL database powered by Cloud SQL. Now you can rapidly build your app with rich queries, complex conditions, and semantic vector search for secure gen AI flows. Data Connect supports secure schema, query and mutation management using GraphQL technology that integrates with Firebase Authentication. Data Connect automatically creates a database schema, secure API server, and typesafe-generated SDKs for Android, iOS, Web, and Flutter applications.
Simplify every stage of your database journey with Gemini
Today, managing a fleet of databases often relies on a disjointed collection of tools, scripts, and error-prone workflows. This fragmented approach is not only costly to maintain but also inefficient and limited in its capabilities. Adding to the complexity, developers and database administrators need to keep their database fleet up-to-date, and learn ever-evolving SQL and NoSQL database technologies.
We set out to simplify every stage of database management with our Gemini models. And to simplify fleet management, we announced Database Center, which offers a single pane of glass for monitoring and operating database fleets at scale, to reduce risks and improve resource utilization. Database Center monitors Google Cloud databases through a single interface across projects and regions — helping you identify potential issues before they impact application performance or database reliability.
Later this month, Spanner will be a supported database in Database Center alongside Cloud SQL and AlloyDB, with additional databases on the way. In addition, we’re making Database Center, with its full database monitoring and operating capabilities, available to anyone. Database Center’s advanced AI-powered capabilities, including intelligent chat, cost optimization and advanced security recommendations, are unlocked once you enable Gemini.
Migrate and modernize your database estate for AI
Legacy databases generally have poor support for gen AI, so you need to modernize them to take advantage of these emerging capabilities. That’s why we partnered with Oracle to help you migrate and supercharge your Oracle workloads on Google Cloud. Just last month, we announced that Oracle Database@Google Cloud is generally available in four Google Cloud regions: US East (Ashburn), US West (Salt Lake City), UK South (London), and Germany Central (Frankfurt). Today we’re announcing that the addition of the South America East (Sao Paulo) region will be available in the coming months, and we’ll more than double the number of regions we currently operate in through 2025.
“Dun & Bradstreet is a global leader in business decisioning data and analytics. With the unparalleled quality of D&B data, we can now seamlessly integrate Oracle Database’s performance, reliability, and scalability with Google Cloud’s powerful analytics and AI tools. This synergy allows us to process and analyze massive datasets with unprecedented speed and efficiency, extract deeper insights, and deliver more value to our customers.” – Adam Fayne, VP, Enterprise Engineering, Dun & Bradstreet
Embracing the future
Our message to you is clear: the future of AI is here, and it’s accessible to every developer and enterprise. With a robust infrastructure, innovative database solutions, and AI-powered assistance, we’re paving the way for a new era of intelligent applications. Learn more about Google Cloud databases and Google’s Data Cloud.
AI Summary and Description: Yes
Summary: The text discusses Google’s innovations in generative AI (gen AI) applications through enhanced database solutions and partnerships. It emphasizes the importance of operational data for developers and how improvements in databases like AlloyDB and Memorystore can support AI-driven applications across various cloud environments.
Detailed Description:
The discussed text highlights Google’s efforts in optimizing and modernizing database technologies to better support generative AI applications in enterprise settings. Here are the significant points:
– **Importance of Operational Data**: The text underscores that developers are crucial to successfully implementing gen AI in enterprises. With many more software developers than data scientists, the emphasis is on tools that facilitate developers’ work in AI application development.
– **Innovations in Databases**:
– Google Cloud offers features like vector search and LangChain integration across all databases, enabling the development of smart applications.
– **AlloyDB Enhancements**: AlloyDB has been upgraded to include advanced features such as the ScaNN vector index, which supports handling over a billion vectors while maintaining high performance. This positions AlloyDB as a vital resource for enterprises looking to build AI applications.
– **Cross-Cloud Management**: The launch of AlloyDB Omni, a downloadable version that operates across various cloud environments, illustrates Google’s commitment to flexible database management in multi-cloud operations. Aiven for AlloyDB Omni presents a managed service for users across platforms like Google Cloud, AWS, and Azure.
– **Memory and Performance Improvements**:
– Google introduced Memorystore for Valkey, achieving high throughput with low latency, especially for vector workloads. The advancements in Memorystore, such as the introduction of version 8.0, include substantial performance enhancements.
– **Firebase Enhancements**: With the introduction of Firebase Data Connect, Google is expanding capabilities for developers to create AI-driven applications, complemented by secure data management features.
– **Unified Database Management**: The launch of Database Center aims to simplify database fleet management, providing comprehensive monitoring and operational capabilities while helping identify potential issues before affecting performance.
– **Migration and Modernization**: Google emphasizes the need for organizations to modernize their existing databases for better support of gen AI functionalities, illustrated by their partnership with Oracle for migrating Oracle workloads to Google Cloud.
– **Future Vision**: The text concludes with a strong message that AI is becoming more accessible for developers and businesses, facilitated by robust infrastructure and innovative solutions from Google Cloud.
Overall, the text outlines how Google Cloud is positioning itself as a leader in enabling enterprises to leverage generative AI effectively through advanced database technologies and enhanced operational capabilities. The implications for security and compliance professionals lie in ensuring that these new database architectures maintain data integrity, security, and comply with regulatory standards across various cloud environments.