[[["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)：2025-08-20。"],[[["\u003cp\u003eFirestore in Datastore mode (Datastore) is a NoSQL document database designed for automatic scaling, high performance, and easy application development.\u003c/p\u003e\n"],["\u003cp\u003eDatastore offers features like atomic transactions, high availability, massive scalability, flexible data storage and querying, strong consistency, encryption at rest, and is fully managed with no planned downtime.\u003c/p\u003e\n"],["\u003cp\u003eUnlike relational databases, Datastore is schemaless and designed to automatically scale to very large datasets, supporting only queries that scale with the result set size.\u003c/p\u003e\n"],["\u003cp\u003eDatastore is ideal for applications requiring highly available structured data at scale, such as product catalogs, user profiles, and ACID transactions.\u003c/p\u003e\n"],["\u003cp\u003eAlternative database options to Datastore are recommended for relational databases with full SQL support, non-structured data, interactive querying, or large immutable blobs such as images or movies.\u003c/p\u003e\n"]]],[],null,["# Datastore Overview\n\n| This API is supported for first-generation runtimes and can be used when [upgrading to corresponding second-generation runtimes](/appengine/docs/standard/\n| go\n| /services/access). If you are updating to the App Engine Go 1.12+ runtime, refer to the [migration guide](/appengine/migration-center/standard/migrate-to-second-gen/go-differences) to learn about your migration options for legacy bundled services.\n\n\u003cbr /\u003e\n\nFirestore in Datastore mode (Datastore) is a NoSQL document database built for automatic scaling, high performance,\nand ease of application development. Datastore features include:\n\n- **Atomic transactions**. Datastore can execute a set of operations where either all succeed, or none occur.\n- **High availability of reads and writes**. Datastore runs in Google data centers, which use redundancy to minimize impact from points of failure.\n- **Massive scalability with high performance**. Datastore uses a distributed architecture to automatically manage scaling. Datastore uses a mix of indexes and query constraints so your queries scale with the size of your result set, not the size of your dataset.\n- **Flexible storage and querying of data** . Datastore maps naturally to object-oriented and scripting languages, and is exposed to applications through multiple clients. It also provides a SQL-like [query language](/datastore/docs/apis/gql/gql_reference).\n- **Strong consistency**. Datastore ensures that all queries are strongly consistent.\n- **Encryption at rest** . Datastore automatically encrypts all data before it is written to disk and automatically decrypts the data when read by an authorized user. For more information, see [Server-Side Encryption](/datastore/docs/concepts/encryption-at-rest).\n- **Fully managed with no planned downtime**. Google handles the administration of the service so you can focus on your application. Your application can still use Datastore when the service receives a planned upgrade.\n\nComparison with relational databases\n------------------------------------\n\nWhile the Datastore interface has many of the same features\nsimilar to relational databases, as a NoSQL database, it varies in how it\ndescribes the relationships between data objects. Here's a high-level comparison\nof Datastore and relational database concepts:\n\nUnlike rows in a relational database table, Datastore entities of\nthe same kind can have different properties, and different entities can have\nproperties with the same name but different value types. These unique\ncharacteristics imply a different way of designing and managing data to take\nadvantage of the ability to scale automatically. In particular,\nDatastore differs from a traditional relational database in the\nfollowing important ways:\n\n- Datastore is designed to automatically scale to very large data sets, allowing applications to maintain high performance as they receive more traffic:\n - Datastore writes scale by automatically distributing data as necessary.\n - Datastore reads scale because the only queries supported are those whose performance scales with the size of the result set (as opposed to the data set). This means that a query whose result set contains 100 entities performs the same whether it searches over a hundred entities or a million. This property is the key reason some types of queries are not supported.\n- Because all queries are served by previously built indexes, the types of queries that can be executed are more restrictive than those allowed on a relational database with SQL. In particular, Datastore does not include support for join operations, inequality filtering on multiple properties, or filtering on data based on results of a subquery.\n- Unlike relational databases which enforce a schema, Datastore is schemaless. It doesn't require entities of the same kind to have a consistent set of properties (although you can choose to enforce such a requirement in your own application code).\n\nWhat it's good for\n------------------\n\nDatastore is ideal for applications that rely on highly available structured data at scale. You can use Datastore to store and query all of the following types of data:\n\n- Product catalogs that provide real-time inventory and product details for a retailer.\n- User profiles that deliver a customized experience based on the user's past activities and preferences.\n- Transactions based on [ACID](https://en.wikipedia.org/wiki/ACID) properties. For example, transferring funds from one bank account to another.\n\nOther storage and database options\n----------------------------------\n\nDatastore is not ideal for every use case. For example, Datastore is not a relational database, and it is not an effective solution for analytic data.\n\nHere are some common scenarios where you should probably consider an alternative to Datastore:\n\n- If you need a relational database with full SQL support for an online transaction processing (OLTP) system, consider [Cloud SQL](/sql).\n- If you don't require support for ACID transactions or if your data is not highly structured, consider [Bigtable](/bigtable).\n- If you need interactive querying in an online analytical processing (OLAP) system, consider [BigQuery](/bigquery).\n- If you need to store large immutable blobs, such as large images or movies, consider [Cloud Storage](/storage).\n\n\nFor more information about other database options, see the [overview\nof database services](/products/databases).\n\nWhat's next\n-----------\n\n- [Learn how to store and query data using the Google Cloud console](/datastore/docs/store-query-data)\n- [Learn about the Datastore data model](/datastore/docs/concepts/entities)\n- [View best practices for Datastore](/datastore/docs/best-practices)\n\nConnecting to Datastore with App Engine\n---------------------------------------\n\nApp Engine's Go standard runtime connects to Datastore using the [Go\nDatastore API](/appengine/docs/legacy/standard/go111/datastore/api-overview). For a complete list of the contents of the\n`datastore` package, see the [`datastore` package reference](/appengine/docs/legacy/standard/go111/reference/latest/datastore).\n\nYou cannot use the [Cloud\nDatastore client library](/datastore/docs/reference/libraries#client-libraries-install-go) with Go applications in the App Engine standard\nenvironment."]]
