Gemini: how to link AI assistants to databases and internal systems securely

Gemini has become a central part of Google’s enterprise ecosystem, offering seamless integrations with databases, data warehouses, and internal systems. By combining Gemini 2.5 Pro’s advanced reasoning capabilities with tools like BigQuery Engine Agent, Cloud SQL Studio, Vertex AI Agentspace, and secure connectors, organizations can build AI-powered workflows that analyze data, generate SQL, manage migrations, and even process real-time streams. This guide explores the latest integration features, security options, and usage limits as of August-September 2025.

BigQuery Engine Agent enables natural language data analysis.

The BigQuery Engine Agent integrates Gemini directly into BigQuery, allowing users to interact with their datasets in natural language while automatically generating optimized SQL queries.

• Launch date: Announced at Google Cloud Next (Apr 2025).

• Latest update: 20 Aug 2025 release expanded support for 1M-token context windows.

• Core capabilities:

  • Translate natural language into precise BigQuery SQL.

  • Perform schema discovery and suggest optimal joins automatically.

  • Generate charts and summaries from query results.

• Usage limits:

  • 24 jobs/min by default, upgradeable to 30 jobs/min.

  • Maximum 1,000 query tokens per statement.

• Ideal use case: Data analysts and business teams needing fast insights without manually writing SQL.

By integrating Gemini into BigQuery’s console, teams can ask data questions conversationally, generate rich dashboards, and create views without deep SQL expertise.

Cloud SQL Studio adds Gemini-powered SQL assistance.

Cloud SQL Studio extends Gemini’s capabilities to MySQL and PostgreSQL instances, embedding AI-driven code assistance directly within the Cloud SQL editor.

• Launch date: Documentation released 16 Aug 2025; full GA expected October 2025.

• Features included:

  • SQL generation based on contextual prompts.

  • Query explanations for debugging and optimization.

  • Schema-aware code suggestions for complex joins.

• Usage limits:

  • 64k-token context window per query editor session.

  • Permissions and database visibility are managed through Cloud IAM roles.

• Security controls: Gemini does not store or retain sensitive data from private Cloud SQL instances.

This integration simplifies working with transactional databases by combining Gemini’s reasoning capabilities with native security and IAM enforcement.

Databricks-to-BigQuery migration is streamlined with Gemini.

For enterprises moving from Databricks to BigQuery, Google introduced a Gemini-powered SQL translation tool in August 2025.

• Latest update: Released 22 Aug 2025 as part of Gemini Labs.

• Capabilities:

  • Automatically converts Spark SQL notebooks into BigQuery-compliant SQL.

  • Highlights syntax differences and provides inline migration recommendations.

• Limitations:

  • Only supports notebooks up to 500 KB in size.

  • Users must manually validate the translated code before execution.

This feature dramatically accelerates data warehouse migrations by reducing manual rewriting, especially for organizations consolidating analytics into Google Cloud’s BigQuery ecosystem.

Vertex AI Agentspace brings enterprise-grade database agents.

Vertex AI Agentspace is Google’s framework for creating autonomous AI agents that interact with databases and internal systems.

• Launch date: General availability in May 2025; latest model upgrade 18 Aug 2025.

• Capabilities:

  • Agents can query databases, build dashboards, and generate advanced analytics.

  • Integrated Python execution for running data transformations directly within the environment.

  • Supports BigQuery, Cloud SQL, and third-party APIs.

• Usage limits:

  • Default cap: 1M tokens per run (upgradeable upon request).

  • 5 concurrent executions per agent by default.

• Security features:

  • Enterprise connectors support role-based IAM policies.

  • Audit logs automatically stored in Cloud Logging.

Vertex AI Agentspace is ideal for automating repetitive tasks and building self-updating insights pipelines for enterprise data teams.

Gemini Live API enables real-time database streaming.

For organizations requiring low-latency data processing, Gemini’s Live API connects AI-driven workflows to real-time databases and event-driven infrastructures.

• Launch date: Public preview began Aug 2025.

• Core capabilities:

  • Stream live queries from Cloud Spanner, BigQuery, or IoT telemetry databases.

  • Trigger downstream tasks using Pub/Sub pipelines.

  • Apply continuous Gemini-powered anomaly detection in manufacturing and monitoring environments.

• Performance metrics:

  • Default throughput: 60,000 tokens per minute.

  • Guaranteed latency SLA: ≤400 ms p95.

This makes the Live API critical for industries like finance, e-commerce, factory automation, and supply chain management, where real-time insights are essential.

Secure connectors integrate on-premise databases with Gemini.

Many enterprises need Gemini to work with internal systems and on-premise data stores without exposing sensitive environments to the public internet.

• Feature name: Agentspace Secure Connectors.

• Launch date: Announced Apr 2025 as part of Gemini’s enterprise security enhancements.

• Supported data sources:

  • Oracle

  • SAP HANA

  • MongoDB

  • Proprietary on-prem SQL engines.

• Key capabilities:

  • Uses Private Service Connect (PSC) to route traffic privately.

  • Ensures zero data egress outside the organization’s VPC.

  • Full auditability through Cloud Logging for compliance.

These secure connectors allow enterprises to safely integrate Gemini into sensitive environments like finance, healthcare, and government infrastructures.

Gemini Code Assist simplifies database migrations and automation.

In August 2025, Gemini extended its Code Assist functionality to database-related workflows via GitHub-integrated automation:

• Capabilities:

  • Generates database migration scripts automatically during pull requests.

  • Provides inline SQL linting for frameworks like SQLAlchemy and Prisma.

  • Automates schema synchronization across environments.

• Usage model:

  • Free for public repositories.

  • Private repos count toward the 25,000 AI credit/month quota for Gemini Pro subscribers.

This makes Gemini Code Assist especially valuable for engineering teams handling multi-database environments and CI/CD-driven schema evolution.

Comparing Gemini’s database and internal integration options.

Integration	Latest Update	Core Capability	Context / Throughput	Best For
BigQuery Engine Agent	Aug 2025	Natural-language → SQL queries & charting	1M-token ctx · 24 jobs/min	Analytics teams
Cloud SQL Studio	Aug 2025	AI-powered SQL authoring for MySQL/Postgres	64k-token ctx	DB admins & developers
Databricks→BQ Translator	Aug 2025	Migrates Spark SQL notebooks into BigQuery SQL	500KB per notebook	Data platform teams
Vertex AI Agentspace	Aug 2025	Build multi-system autonomous agents	1M-token ctx · 5 runs	Enterprise automation
Gemini Live API	Aug 2025	Streaming queries & real-time detection	60k TPM · 400 ms SLA	IoT & real-time analytics
Secure Connectors	Apr 2025	Private Service Connect to on-prem DBs	VPC-only · logged	Regulated industries
Gemini Code Assist	Aug 2025	Automates DB migrations inside pull requests	25k AI credits/mo	DevOps & CI/CD pipelines

Choosing the right Gemini integration.

Scenario	Recommended Tool	Why
Conversational analytics for BI	BigQuery Engine Agent	Query data in natural language with automatic charting.
SQL-heavy app development	Cloud SQL Studio	Contextual SQL prompts and schema-aware suggestions.
Migrating from Databricks	Databricks Translator	Accelerates SparkSQL → BigQuery SQL transitions.
Automating enterprise insights	Vertex AI Agentspace	Build agents that fetch, process, and deliver reports autonomously.
Processing IoT or live telemetry	Gemini Live API	Ensures low-latency analysis with scalable streaming support.
Connecting on-premise systems	Agentspace Secure Connectors	Ensures private routing and regulatory compliance.
Automating migration workflows	Gemini Code Assist	Integrates directly with GitHub pipelines for database CI/CD.

Gemini now provides one of the most robust enterprise integration ecosystems for linking AI assistants to databases, data warehouses, on-prem systems, and real-time pipelines. With tools like BigQuery Engine Agent, Agentspace, and secure connectors, enterprises can build AI-powered, compliant workflows that unify structured data, automate reporting, and streamline migrations.

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