Oracle accelerates multi-cloud strategy: AI database services expand to 22 regions, cross-cloud dedicated lines officially enter commercial use.

Oracle's Multi-Cloud Strategy Advances Further: AI Database and Cross-Cloud Interconnect Progress on Two Fronts

Over the past week, Oracle has been the most active player in the multi-cloud arena. From Oracle Interconnect for AWS becoming generally available, to AI Database@AWS adding São Paulo, Madrid, Stockholm, and San Jose regions, to OCI GoldenGate landing on Google Cloud, Oracle is demonstrating through action that true multi-cloud is not about "one cloud consuming everything," but rather about letting the most suitable workloads run on the most suitable clouds while eliminating the friction of cross-cloud connections.

For CTOs and architects who are evaluating enterprise IT architecture, these updates send a clear signal: the major cloud vendors are shifting from "going it alone" to "joint services," and the combination of multi-cloud and AI databases is becoming the new foundation for enterprise digital transformation.

Event Background: Dense Updates on the Official Oracle Blog

According to information published on the Oracle Cloud Infrastructure official blog (May to July 2026), Oracle is advancing its multi-cloud strategy across different regions and markets:

• Oracle Interconnect for AWS: After a limited availability phase, it was announced as generally available (GA) on July 29, 2026, with initial regions in OCI Ashburn and AWS US East (Northern Virginia). The service provides private, high-speed, fully managed cross-cloud connections, with MACsec encryption enabled by default and no data transfer fees.
• Oracle AI Database@AWS: The service marked its first anniversary in June 2026, having expanded to 20 regions at that time. Subsequently, on June 23, Stockholm and San Jose were added, and in July São Paulo and Madrid were added, bringing the current total to 22 regions. The service supports Oracle RAC, Exadata Database Service, Autonomous AI Lakehouse, and native AI Vector Search.
• OCI GoldenGate on Google Cloud: On May 20, 2026, OCI GoldenGate became generally available as part of Oracle AI Database@Google Cloud. Users can configure it directly in the Google Cloud console and pay for it using Google Cloud committed spend discounts.These updates are not isolated pieces of news; they are continuous moves in Oracle’s “multi-cloud first” strategy. The core logic is to embed Oracle’s database and AI capabilities into other mainstream public clouds, so customers do not need to “migrate or re-architect,” but can obtain Oracle’s enterprise-grade data services in their existing cloud environments.

Technical Analysis: From “Dedicated Line Between Two Clouds” to “Database as a Service”

1. Oracle Interconnect for AWS: Taking the Complexity Out of Cross-Cloud Networking

Cross-cloud connectivity is not a new concept. In the past, to communicate between OCI and AWS, enterprises either used the public internet (posing security and latency risks), or they had to build their own VPN or lease a dedicated line, then deal with complicated matters such as inconsistent routing protocols on both sides, managing multiple contracts, and configuring third-party devices. Oracle Interconnect for AWS changes this situation.

The service was jointly designed and operated by Oracle and AWS. It uses a managed connection model with low, globally uniform pricing, no data transfer fees, and IEEE 802.1AE MACsec encryption enabled by default. Customers can create and manage connections through standard cloud consoles, while the underlying network complexity is handled by the two cloud vendors. Essentially, this is a managed upgrade of “cross-cloud VPC peering,” allowing enterprises running distributed architectures to avoid spending excessive effort on the network layer.

2. Oracle AI Database@AWS: Let Enterprise Databases Take Root in AWS

Oracle AI Database@AWS is not a simple “database IP migration,” but a managed service running inside AWS data centers (closely coupled with AWS through OCI infrastructure). Customers can continue to use AWS tools and unified billing while running Oracle RAC, Exadata, Autonomous AI Lakehouse, and more.

Its highlight lies in the word “AI”: Oracle integrates capabilities such as AI Vector Search and Autonomous AI Lakehouse directly with the database, enabling enterprises to run AI workloads right where their business data is stored, without having to copy data to a separate AI data warehouse. This solves the biggest pain point for enterprises building AI—data silos and redundant data movement.

3. OCI GoldenGate on Google Cloud: Real-Time Data Synchronization Becomes the Multi-Cloud Glue OCI GoldenGate is a change data capture and real-time replication service. Now, as part of Oracle AI Database@Google Cloud, it can be configured directly from the Google Cloud console. This means customers can keep data synchronized across multi-cloud environments for database migration, disaster recovery, and real-time analytics. For multi-cloud architectures, real-time data replication is a key tool for eliminating data silos.

Enterprise Impact Analysis: Reducing Cross-Cloud Complexity While Reassessing Costs and Vendor Lock-in

Cost Impact

Oracle Interconnect for AWS's pricing model is worth attention: a unified low-cost connection fee, with data transfer fees waived. In contrast, egress traffic charges from traditional cloud vendors have always been a hidden cost that cannot be ignored in multi-cloud architectures. This design will most likely significantly reduce OPEX for cross-cloud data flows.

However, enterprises still need to pay attention to other costs: after connecting to multi-cloud services, how will database license and support costs be calculated? Will Oracle AI Database@AWS's billing model be consolidated into the AWS bill? Although detailed pricing has not yet been disclosed, enterprises should be prepared to conduct a TCO analysis, especially in comparison with on-premises data centers and single-cloud solutions.

Deployment and Operations Impact

The biggest advantage is reducing the risk of "re-architecting." In the past, migrating Oracle databases to other cloud platforms often required modifying applications or the database architecture. Now, through AI Database@AWS or Google Cloud, enterprises can retain their Oracle environment while enjoying the ecosystem services of AWS or Google Cloud. Operations teams can still use AWS's monitoring, identity, and network tools, resulting in a gentle learning curve.

But please note: these services are still in a phase of rapid evolution, and the pace of regional expansion is uneven. Currently, Oracle AI Database@AWS is only available in some regions with a single availability zone, which may not meet high-availability requirements. When adopting these services, enterprises should assess regional availability and formulate appropriate disaster recovery strategies.

Security and Compliance

Oracle Interconnect for AWS enables MACsec encryption by default, ensuring the confidentiality and integrity of data transmitted between clouds. At the same time, by using managed connections that bypass the public internet, it reduces the risk of DDoS and man-in-the-middle attacks. For cross-border data compliance, Oracle and AWS are continuously expanding regional coverage (such as Madrid and São Paulo) to support data residency requirements. However, enterprises still need to verify for themselves whether cross-border data transfers comply with local regulations (such as GDPR, PDPB, etc.) and cannot fully rely on cloud providers' "coverage."

Overall RecommendationsThese multi-cloud services are suitable for companies that: - Are “dual-stack” enterprises with substantial applications on AWS or Google Cloud while also running critical databases on Oracle; - Are Oracle customers that want to use AI capabilities without migrating their databases; - Are planning database migration and prefer a phased strategy rather than a “big bang” switch.

Conversely, if an enterprise does not use Oracle databases, or has concerns about Oracle licensing, its value is limited.

Market Competition Analysis: A New Paradigm of Oligopolistic Co-opetition

In traditional cloud competition, vendors try to keep workloads within their own ecosystems. But Oracle’s strategy this time is completely different: since database workloads are difficult to migrate wholesale, it may as well proactively “enter” competitors’ territory and become a “value-added layer” on other clouds.

• AWS and Oracle: “Frenemies”: AWS has repeatedly pushed customers to migrate from Oracle databases to Aurora or PostgreSQL, but now the two sides jointly offer Oracle database services. This shows that in the AI era, the most profitable enterprise workloads (database + AI) cannot be locked in by infrastructure alone; cooperation actually expands competition with data companies such as Snowflake and Databricks.
• Potential Impact on Azure: Oracle also has a similar partnership with Azure (Oracle Database@Azure), but this high-profile expansion by AWS may lead some Oracle customers on Azure to reassess. However, Azure still has its own advantages, especially deep integration with Office 365 and Active Directory.
• Google Cloud’s Differentiation: Through OCI GoldenGate, Google Cloud gains real-time data replication capabilities, attracting customers who need to span Oracle and Google Cloud. This partnership makes Google Cloud more competitive in data integration and AI.
• Impact on Smaller Cloud Vendors and Managed Service Providers: Cooperation among top-tier cloud vendors competes with existing managed service providers (such as Rackspace), which previously relied on “helping customers connect multiple clouds” as their service. Now that Oracle and AWS are operating jointly, the space for third-party intermediaries in the middle will be compressed.

The real beneficiaries are large “multi-cloud enterprises” — they can gain more options without changing their existing cloud investments. And single-cloud vendor lock-in, especially lock-in built around databases, is being replaced by this kind of “strategic partnership lock-in.”

Industry Trend Observation: AI-Native Multi-Cloud Architecture, with Database as the Core HubIn the past, multi-cloud architecture was typically understood as the cross-cloud distribution of compute and storage. But in the AI era, data has become the most important asset, and the database, as the heart of data, has become the core hub of multi-cloud strategy.

Oracle's strategy reflects three major trends:

1. AI cloud moves to "where the data resides": Instead of moving databases next to GPUs, AI capabilities are built into the databases themselves, continuously providing enterprises with a foundation for intelligent analytics. 2. Cloud providers shift from "mutual exclusion" to "interconnection": The infrastructure layer is beginning to standardize and commoditize, and the key to differentiation lies in which advanced services and partner networks a provider offers. 3. Enterprise IT strategy becomes a "cloud network": It is no longer about choosing a single cloud, but about designing a topology where connections, data flows, and security boundaries span multiple clouds. Cloud-native services and managed connections will become part of the infrastructure, just like roads.

In the long run, "interconnectivity" among cloud providers will become the standard, not just the exception. Cloud platforms that cannot deliver a seamless cross-cloud experience may lose share among large enterprise customers. Oracle appears to have realized this and is rapidly building out its own multi-cloud "connectivity map."

CloudTechDaily Insight

The essence of Oracle's dense release this time is not a simple "product update," but rather a reshaping of the rules of the cloud computing industry—replacing "lock-in" with "interoperability."

The most important message is that advanced AI database services can be deployed not only on OCI, but also on AWS and Google Cloud, without sacrificing functionality. The impact on enterprise IT strategy is multi-dimensional. First, it lowers the cognitive burden of switching cloud providers, making technology decisions more based on business value rather than physical location. Second, it means enterprises can evolve their IT in an "incremental" way, gradually integrating AI capabilities into existing databases, rather than undertaking a one-time cloud migration. Third, it challenges traditional notions that equate Oracle databases with "cloud-agnostic" or "self-hosted" environments.

In the future, the competitiveness of cloud platforms will depend on how open they are on the "data plane" and whether they are willing to serve customers collaboratively with other rivals. Oracle is doing this not to abandon its own multi-region cloud, but to allow its leading position in AI database technology to permeate all major cloud ecosystems. For enterprises, this brings ample choice, but also demands stronger cross-cloud governance and architecture capabilities. Multi-cloud is no longer the future tense, but the present progressive, and the database has become the new hub in an AI-driven multi-cloud world.