# AlloyDB for PostgreSQL documentation [Read product documentation](https://docs.cloud.google.com/alloydb/docs/overview.md.txt) AlloyDB is a fully-managed, PostgreSQL-compatible database for demanding transactional workloads. It provides enterprise-grade performance and availability while maintaining 100% compatibility with open-source PostgreSQL. [Go to the AlloyDB for PostgreSQL product page for more.](https://cloud.google.com/alloydb/) Not sure what database option is right for you? Learn more about our [database services](https://cloud.google.com/products/databases). ## Documentation resources Find quickstarts and guides, review key references, and get help with common issues. ### Get started - [AlloyDB overview](https://docs.cloud.google.com/alloydb/docs/overview.md.txt) - [AlloyDB AI tutorials, codelabs, and notebooks](https://docs.cloud.google.com/alloydb/docs/ai/alloydb-ai-use-cases.md.txt) - [Create and connect to a database](https://docs.cloud.google.com/alloydb/docs/quickstart/create-and-connect.md.txt) - [Connect from Google Kubernetes Engine (GKE) to AlloyDB](https://docs.cloud.google.com/alloydb/docs/quickstart/integrate-kubernetes.md.txt) - [Grant AlloyDB access to other users](https://docs.cloud.google.com/alloydb/docs/user-grant-access.md.txt) - [Perform a vector search](https://docs.cloud.google.com/alloydb/docs/ai/perform-vector-search.md.txt) - [Integrate AlloyDB with Gemini Enterprise Agent Platform](https://docs.cloud.google.com/alloydb/docs/ai/configure-vertex-ai.md.txt) ### Guides - [Accelerate queries using the columnar engine](https://docs.cloud.google.com/alloydb/docs/columnar-engine/about.md.txt) - [Analyze performance using Query Insights](https://docs.cloud.google.com/alloydb/docs/query-insights-overview.md.txt) - [Build generative AI applications using AlloyDB AI](https://docs.cloud.google.com/alloydb/docs/ai.md.txt) - [Connect a psql client](https://docs.cloud.google.com/alloydb/docs/connect-psql.md.txt) - [Connect securely using the Auth proxy](https://docs.cloud.google.com/alloydb/docs/auth-proxy/overview.md.txt) - [Create a read pool instance](https://docs.cloud.google.com/alloydb/docs/instance-read-pool-create.md.txt) - [Scale an instance](https://docs.cloud.google.com/alloydb/docs/instance-read-pool-scale.md.txt) - [Configure backup plans](https://docs.cloud.google.com/alloydb/docs/backup/configure.md.txt) ### Reference \& Resources - [gcloud CLI reference](https://docs.cloud.google.com/sdk/gcloud/reference/beta/alloydb.md.txt) - [IAM roles and permissions](https://docs.cloud.google.com/alloydb/docs/reference/iam-roles-permissions.md.txt) - [Locations](https://docs.cloud.google.com/alloydb/docs/locations.md.txt) - [Pricing](https://docs.cloud.google.com/alloydb/pricing) - [Quotas and limits](https://docs.cloud.google.com/alloydb/quotas.md.txt) - [Release notes](https://docs.cloud.google.com/alloydb/docs/release-notes.md.txt) - [REST API reference](https://docs.cloud.google.com/alloydb/docs/reference/rest.md.txt) - [Supported database flags](https://docs.cloud.google.com/alloydb/docs/reference/database-flags.md.txt) ## Related resources Training and tutorials Use cases Explore self-paced training, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services. Codelab Training and tutorials ### [AlloyDB AI Embedding lab](https://codelabs.developers.google.com/codelabs/alloydb-ai-embedding) Get hands-on practice with creating and using vector embeddings using AlloyDB. This codelab guides you through setting up an AlloyDB cluster, integrating it with Gemini Enterprise Agent Platform, and then applying a generative model to data queries. 107 minutes Introductory Free
Training Training and tutorials ### [Semantic search with AlloyDB PG_Vector](https://explore.qwiklabs.com/focuses/7136?parent=catalog) This lab walks you through building a semantic search web application for searching through movie plot summaries using AlloyDB vector search to find movies and similar movies. Signing in to Google Cloud Qwiklabs is required to access this lab. 135 minutes Introductory Free
Whitepaper Use cases ### [Whitepaper: ScaNN for AlloyDB for PostgreSQL](https://services.google.com/fh/files/misc/scann_for_alloydb_whitepaper.pdf) Explains how ScaNN for AlloyDB for PostgreSQL achieves faster performance and improves memory footprint. ScaNN vector search vector embeddings vector indexing
Best practice Use cases ### [Best practices for tuning ScaNN indexes](https://docs.cloud.google.com/alloydb/docs/ai/best-practices-tuning-scann.md.txt) Provides recommendations about how to tune index parameters for optimal balance between recall and QPS. ScaNN optimization
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