Generative AI isn’t just for composing emails and creating presentations; the power of AI is also coming to databases. It can help solve complex issues with database management, from migration and modernization to optimization, making queries faster and more efficient—even for those lacking Structured Query Language (SQL) skill sets.
These days, the majority of IT teams typically use more than one database platform; indeed, most use multiple database platforms to handle different requirements. But this database sprawl results in a much more complex environment, making it more difficult to manage.
The role of GenAI in database management
That’s where GenAI can play a role. For example, querying a database has typically required knowledge of SQL and/or other database query languages. Now, however, with the use of GenAI, you can make queries using natural language (and get answers in natural language).
Even if you’re well versed in SQL, GenAI can be used for database query optimization, making queries easier and faster. For example, it can help write and debug queries against complex datasets, resulting in faster data analysis times.
In the Google Cloud ecosystem, Gemini for Databases—an AI-powered assistant for databases—can simplify all aspects of the database journey, from developing database-driven applications to optimization, management, security, governance, and migrations.
Specifically, Google has three database solutions: Database Studio, an SQL editor in the Google Cloud console; Database Center, which allows you to manage an entire fleet of databases from a single pane of glass; and Database Migration Service, which can assist with cloud migrations.
5 key benefits of Gemini for Databases include:
Develop applications faster: With Database Studio, you can generate SQL code with intelligent code assistance and code completion—even using natural language to build applications.
Optimize performance: Using Database Insights, Gemini analyzes workloads and highlights any issues—such as missing indexes and resource bottlenecks—so you can leverage recommendations to optimize performance.
Mitigate risks: With Database Center, an AI-enhanced dashboard provides a central view of your entire database fleet, allowing you proactively monitor instances. With predictive analytics capabilities, it can also alert you to potential performance issues.
Improve security and compliance: With Database Center, security is made easier with automated scans, providing near-real-time analysis of potential attack vectors. It also provides recommendations to mitigate risks, which can improve network security, access management, and audit capabilities.
Accelerate database migrations: With Gemini in Databases, you can streamline migrations with automated code and database conversions. For example, Gemini can convert database-resident code to a PostgreSQL dialect, and Gemini in Database Migration Service can ‘learn’ from the user to help with last-mile code conversion.
How Pythian can help
While GenAI holds great potential, many business leaders and IT teams have concerns about AI, from data security to the accuracy of results.
That’s where a partner with database experience—and Generative AI expertise—can help. The Pythian framework, for example, provides cost-effective GenAI discovery, proof of concept, and production offerings in concert with existing data services.
And, with 25+ years of data experience, Pythian can also provide technical and business advice including database design and database version recommendations. Pythian’s Database Consulting Services can help your team reduce risk, improve performance, and convert data into value.
Want to unlock more value from your Google Cloud databases? Contact us at info@pythian.com.
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