AlloyDB for PostgreSQL 文档
AlloyDB 是一种与 PostgreSQL 兼容的全托管式数据库，适用于要求苛刻的事务型工作负载。它可提供企业级性能和可用性，同时与开源 PostgreSQL 保持 100% 兼容。
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培训
培训和教程
AlloyDB AI 嵌入实验
通过使用 AlloyDB 创建和使用向量嵌入来进行实操练习。本 Codelab 将引导您设置 AlloyDB 集群，将其与 Vertex AI 集成，然后将生成模型应用于数据查询。
107 分钟
简介
免费
培训
培训和教程
使用 AlloyDB PG_Vector 进行语义搜索
本实验将引导您构建语义搜索 Web 应用，以便使用 AlloyDB 向量搜索来搜索电影情节摘要，从而查找电影和类似电影。需要登录 Google Cloud Qwiklabs 才能访问此实验。
135 分钟
简介
免费
使用场景
使用场景
白皮书：ScaNN for AlloyDB for PostgreSQL
说明 ScaNN for AlloyDB for PostgreSQL 如何实现更快的性能并减少内存占用。
ScaNN
向量搜索
向量嵌入
向量索引编制
使用场景
使用场景
调优 ScaNN 索引的最佳实践
提供有关如何对索引参数进行调优以在召回率和 QPS 之间取得最佳平衡的建议。
ScaNN
优化
如未另行说明，那么本页面中的内容已根据知识共享署名 4.0 许可获得了许可，并且代码示例已根据 Apache 2.0 许可获得了许可。有关详情，请参阅 Google 开发者网站政策。Java 是 Oracle 和/或其关联公司的注册商标。
最后更新时间 (UTC)：2025-08-25。
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-08-25。"],[[["\u003cp\u003eAlloyDB for PostgreSQL is a fully-managed, PostgreSQL-compatible database designed for demanding transactional workloads, providing enterprise-grade performance and availability.\u003c/p\u003e\n"],["\u003cp\u003eAlloyDB offers 100% compatibility with open-source PostgreSQL, allowing seamless integration with existing PostgreSQL tools and applications.\u003c/p\u003e\n"],["\u003cp\u003eAlloyDB AI enables building generative AI applications, performing vector searches, and integrating with Vertex AI, expanding the database's capabilities beyond traditional workloads.\u003c/p\u003e\n"],["\u003cp\u003eComprehensive resources, including quickstarts, guides, reference materials, and training labs, are available to help users get started and optimize their use of AlloyDB.\u003c/p\u003e\n"],["\u003cp\u003eUsers can leverage features like the columnar engine to accelerate queries and Query Insights to analyze performance, improving the overall efficiency and effectiveness of their database operations.\u003c/p\u003e\n"]]],[],null,["# AlloyDB for PostgreSQL documentation\n====================================\n\n[Read product documentation](/alloydb/docs/overview) AlloyDB is a fully-managed, PostgreSQL-compatible database for demanding\ntransactional workloads. It provides enterprise-grade performance and availability\nwhile maintaining 100% compatibility with open-source PostgreSQL.\n\nNot sure what database option is right for you? Learn more about\nour [database services](/products/databases).\n\n[Learn more](/alloydb/docs/overview) about AlloyDB.\n[Get started for free](https://console.cloud.google.com/freetrial) \n\n#### Start your proof of concept with $300 in free credit\n\n- Get access to Gemini 2.0 Flash Thinking\n- Free monthly usage of popular products, including AI APIs and BigQuery\n- No automatic charges, no commitment \n[View free product offers](/free/docs/free-cloud-features#free-tier) \n\n#### Keep exploring with 20+ always-free products\n\n\nAccess 20+ free products for common use cases, including AI APIs, VMs, data warehouses,\nand more.\n\nDocumentation resources\n-----------------------\n\nFind quickstarts and guides, review key references, and get help with common issues. \nfollow_the_signs\n\n### Get started\n\n-\n\n [AlloyDB overview](/alloydb/docs/overview)\n\n-\n\n [AlloyDB AI tutorials, codelabs, and notebooks](/alloydb/docs/ai/alloydb-ai-use-cases)\n\n-\n\n [Create and connect to a database](/alloydb/docs/quickstart/create-and-connect)\n\n-\n\n [Connect from Google Kubernetes Engine (GKE) to AlloyDB](/alloydb/docs/quickstart/integrate-kubernetes)\n\n-\n\n [Grant AlloyDB access to other users](/alloydb/docs/user-grant-access)\n\n-\n\n [Perform a vector search](/alloydb/docs/ai/perform-vector-search)\n\n-\n\n [Integrate AlloyDB with Vertex AI](/alloydb/docs/ai/configure-vertex-ai)\n\nformat_list_numbered\n\n### Guides\n\n-\n\n [Accelerate queries using the columnar engine](/alloydb/docs/columnar-engine/about)\n\n-\n\n [Analyze performance using Query Insights](/alloydb/docs/query-insights-overview)\n\n-\n\n [Build generative AI applications using AlloyDB AI](/alloydb/docs/ai)\n\n-\n\n [Connect a psql client](/alloydb/docs/connect-psql)\n\n-\n\n [Connect securely using the Auth proxy](/alloydb/docs/auth-proxy/overview)\n\n-\n\n [Create a read pool instance](/alloydb/docs/instance-read-pool-create)\n\n-\n\n [Scale an instance](/alloydb/docs/instance-read-pool-scale)\n\n-\n\n [Configure backup plans](/alloydb/docs/backup/configure)\n\ngroup_work\n\n### Reference \\& Resources\n\n-\n\n [gcloud CLI reference](/sdk/gcloud/reference/beta/alloydb)\n\n-\n\n [IAM roles and permissions](/alloydb/docs/reference/iam-roles-permissions)\n\n-\n\n [Locations](/alloydb/docs/locations)\n\n-\n\n [Pricing](/alloydb/pricing)\n\n-\n\n [Quotas and limits](/alloydb/quotas)\n\n-\n\n [Release notes](/alloydb/docs/release-notes)\n\n-\n\n [REST API reference](/alloydb/docs/reference/rest)\n\n-\n\n [Supported database flags](/alloydb/docs/reference/database-flags)\n\nRelated resources\n-----------------\n\nTraining and tutorials \nUse cases \nExplore self-paced training, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services. Training \nTraining and tutorials\n\n### AlloyDB AI Embedding lab\n\n\nGet hands-on practice with creating and using vector embeddings using AlloyDB. This codelab guides you through setting up an AlloyDB cluster, integrating it with Vertex AI, and then applying a generative model to data queries.\n\n\n107 minutes Introductory Free\n\n\u003cbr /\u003e\n\n[Learn more](https://codelabs.developers.google.com/codelabs/alloydb-ai-embedding) \nTraining \nTraining and tutorials\n\n### Semantic search with AlloyDB PG_Vector\n\n\nThis 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.\n\n\n135 minutes Introductory Free\n\n\u003cbr /\u003e\n\n[Learn more](https://explore.qwiklabs.com/focuses/7136?parent=catalog) \nUse case \nUse cases\n\n### Whitepaper: ScaNN for AlloyDB for PostgreSQL\n\n\nExplains how ScaNN for AlloyDB for PostgreSQL achieves faster performance and improves memory footprint.\n\nScaNN vector search vector embeddings vector indexing\n\n\u003cbr /\u003e\n\n[Learn more](https://services.google.com/fh/files/misc/scann_for_alloydb_whitepaper.pdf) \nUse case \nUse cases\n\n### Best practices for tuning ScaNN indexes\n\n\nProvides recommendations about how to tune index parameters for optimal balance between recall and QPS.\n\nScaNN optimization\n\n\u003cbr /\u003e\n\n[Learn more](/alloydb/docs/ai/best-practices-tuning-scann)\n\nRelated videos\n--------------"]]
