Google Cloud Integrates Spanner Graph with Vertex AI
Google Cloud is now integrating Spanner Graph with Vertex AI to streamline AI workflows. Check out more details here!
Key Takeaways
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Google Cloud has released a series of AI-based innovations, including the integration of Spanner Graph with Vertex AI.
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This integration makes it easier for users to access generative AI and predictive models.
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Spanner Graph can now be used in various applications such as social networks, healthcare, transportation, and more.
Google Cloud has launched its latest innovation, integrating Spanner Graph with Vertex AI. Additionally, the Cloud has introduced a series of other innovations that leverage artificial intelligence (AI) to create relevant, fact-based, and accurate applications.
What Is Spanner Graph?
Spanner Graph is a feature that supports a graph query interface compatible with the ISO GQL (Graph Query Language) standard.
Spanner Graph supports interoperability between relational and graph models, combining advanced SQL capabilities with the pattern-matching expressiveness of GQL.
Spanner Graph integrates specialized graph database capabilities with Spanner, offering industry-leading scalability, availability, and consistency.
You can map tables to graphs using a declarative schema without the need for data migration, bringing graph capabilities to tabular datasets.
Additionally, you can dynamically bind data model choices per query, making it easier to select the right tool for your workflow.
Key Capabilities of Spanner Graph
Spanner Graph emphasizes an integrated database that combines graph, relational, search, and AI capabilities with high performance and scalability. Here are the key capabilities of Spanner Graph.
- Scalability, consistency, and availability: Proven and trusted scalability, availability, and consistency of Spanner.
- Native graph experience: Spanner Graph provides a familiar ISO GQL interface designed according to open standards.
- AI-supported workflows: Integrated with Vertex AI, Spanner Graph enables direct access to numerous AI models and accelerates workflows.
- Built-in search capabilities: You can leverage keywords and semantic meanings in graph analysis, as text search is fully supported and enriched with multimedia vectors.
- Integrated relational and graph models: Full interoperability between GQL and SQL eliminates data silos and allows you to choose the best tool for each use case, without operational burdens for extraction, transformation, and loading (ETL).
What’s New from Spanner Graph?
Google Cloud's Spanner Graph has now been integrated with Vertex AI, a fully managed and unified AI development platform for building and using generative AI.
This integration makes it easier for users to access Vertex AI's generative capabilities through Spanner Graph queries and schemas, as well as predictive models. Consequently, users benefit from a streamlined AI workflow.
Furthermore, Spanner has been enhanced with intelligent multi-model database capabilities and seamless collaboration, enabling the creation of new AI-friendly applications.
Spanner Graph can be applied to various use cases, including financial fraud detection, social networks, healthcare, transportation, and customer experience enhancement.
Additionally, Spanner Graph features full-text search and vector search capabilities, leveraging Google's expertise as a search engine to provide advanced full-text search results.
You can select the Spanner edition that aligns with your budget and requirements, choosing from Standard, Enterprise, or Enterprise Plus.
News Sources
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- Google Cloud Indonesia - https://blog.google/intl/id-id/google-cloud-rilis-inovasi-ai-melalui-spanner-graph-terbaru/
- Google Cloud Documentation - https://cloud.google.com/spanner/docs/graph/overview
Alivia Ariatna
As an experienced SEO content writer, I specialize in crafting compelling, keyword-optimized content with extensive research on it. I stay updated with the latest SEO trends and best practices to ensure my content meets both user intent and search engine requirements.
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