Documentación de Firestore en modo Datastore
Firestore en modo Datastore es una base de datos de documentos NoSQL creada para proporcionar ajuste de escala automático, alto rendimiento y facilidad de desarrollo de aplicaciones.
Aunque la interfaz del modo Datastore tiene muchas de las características de las bases de datos tradicionales, difiere de ellas en la forma en que describe las relaciones entre los objetos de datos, debido a que es una base de datos NoSQL.
¿No estás seguro de qué opción de base de datos es la adecuada para ti? Obtén más información sobre nuestros servicios de base de datos.
Comienza tu prueba de concepto con un crédito gratis de USD 300
- Accede a Gemini 2.0 Flash Thinking
- Uso mensual gratuito de productos populares, incluidas las APIs de IA y BigQuery
- Sin cargos automáticos y sin compromisos
Recursos de documentación
Guías
-
Guía de inicio rápido: Almacena y consulta datos en Firestore en modo Datastore
-
Importa y exporta entidades
-
Ejecutar el emulador de Datastore
-
Administrador de Datastore
-
Acceder a tu base de datos
-
Borrar entidades de manera masiva
-
Configuración de índices
-
Visualiza estadísticas en Console
-
Administra Firestore en modo Datastore desde Console
-
Videos relacionados
What's new with the AI Lakehouse
Organizations have been searching for optimal ways to store and analyze vast amounts of structured, unstructured, and semistructured data to handle the increasing volume, latency, resilience, and data-access requirements demanded by cross-functional
Migrate App Engine Users service to Cloud Identity Platform (Module 21)
Serverless Migration Station is a Serverless Expeditions miniseries focused on helping developers modernize their applications running on a Google Cloud serverless compute platform. Module 21 is the second video focused on migrating from the App
Migrating App Engine pull tasks to Cloud Pub/Sub (Module 19)
Serverless Migration Station is a Serverless Expeditions mini-series focused on helping developers modernize their applications running on a Google Cloud serverless compute platform. In Module 19, the second video focused on App Engine pull tasks,
How to design a serverless app
In a previous video (https://goo.gle/3GXFBro) Martin and Sara discussed how to design a user interface for a YouTube comment tracking app. In this video, Martin teams up with Wes to discern which Google Cloud products to use. Watch along and learn
Migrating App Engine Blobstore to Cloud Storage (Module 16)
Serverless Migration Station is a Serverless Expeditions mini-series, focused on helping developers modernize their applications running on a Google Cloud serverless compute platform. In this Module 16, the second video focused on App Engine
Migrating App Engine memcache to Cloud Memorystore (Module 13)
Serverless Migration Station is a Serverless Expeditions mini-series, a set of videos focused on helping developers modernize their applications running on a Google Cloud serverless compute platform. In this Module 13 and second video focused on App
Refactoring a Python 2 Cloud NDB app to Python 3 & Cloud Firestore (Module 9)
Module 9 resources: Codelab → https://goo.gle/3pYGwzA Python 2 START ("mod8") code → https://goo.gle/3j3TyYa Python 3 FINISH ("mod9") code → https://goo.gle/3BCemfZ Serverless Migration Station is a Serverless Expeditions mini-series, designed to
Migrating App Engine push queues to Cloud Tasks (Module 8)
Module 8 references: Codelab → https://goo.gle/3lJMtxF Python 2 START ("mod7") code → https://goo.gle/3kEvtsl Python 2 FINISH ("mod8") code → https://goo.gle/3j3TyYa Serverless Migration Station is a Serverless Expeditions mini-series, designed to
Data modernization with Bayer Crop Science
Bayer Crop Science (BCS), is harnessing the spirit of innovation to shape what’s possible for farmers, partners, and the planet. Hear the history of BCS's regional autonomy that led to disparate systems for customer data. Learn how these challenges
Capturing identity data to drive more equitable outcomes
Personal identity is so important to us as humans, it’s the way an individual thinks about themselves, the way they are viewed by the world, and the characteristics that define them. Better understanding personal identity can empower everyone to
Migrating from Cloud Datastore to Cloud Firestore (Part 1: app migration)
Serverless Migration Station is a mini-series from Serverless Expeditions, designed to help Google Cloud developers modernize their applications running on one of the serverless compute platforms. Cloud Datastore and Cloud Firestore are two NoSQL
Migrating from Google App Engine to Cloud Run with Docker
Codelab → https://goo.gle/3fXl0Fq Python 2 START ("mod2a") code → https://goo.gle/2U89Tle Python 2 FINISH ("mod4a") code → https://goo.gle/2VXj7BI Serverless Migration Station is a Serverless Expeditions mini-series designed to help developers
Google Cloud NDB to Cloud Datastore migration
Migration Module 2 Python 2 repo "mod2a" folder → https://goo.gle/2U89Tle Migration Module 2 Python 3 repo "mod2b" folder → https://goo.gle/3i3kGFq Migration Module 3 Python 2 repo "mod3a" folder → https://goo.gle/3lp4H7U Serverless Migration Station
Migrating from App Engine ndb to Cloud NDB
Serverless Migration Station repo → https://goo.gle/3heRoEK Module 2 codelab → https://goo.gle/3B2XFuZ Serverless Migration Station is a mini-series of Serverless Expeditions, created to help developers modernize their serverless applications from
Migrating from App Engine webapp2 to Flask
Serverless Migration Station Module 0 repo folder → https://goo.gle/3jEuw34 Serverless Migration Station Module 1 repo folder → https://goo.gle/3xfynHx Serverless Migration Station Module 1 codelab → https://goo.gle/3qJJWEo Serverless Migration
Introducing Serverless Migration Station
Serverless Migration Station Module 0 baseline app repo folder → https://goo.gle/3vFsMZG Comparing App Engine first vs. second generation platforms → https://goo.gle/3gNWjfC Google's committed support for legacy App Engine runtimes →
Simplify Cloud Run development with Visual Studio Code
Deploying a Cloud Run service with Visual Studio Code → https://goo.gle/31zSJgD Google Cloud blog → https://goo.gle/3dfzpuk Building a Cloud Run web application and using Visual Studio Code? In this episode of Serverless Toolbox Extended, Martin and
Building a petabyte scale reporting pipeline on GCP
Waze for Cities Data allows Waze global public sector partners, mostly municipal officials or traffic departments, to access visualized traffic analysis dashboards with connected-citizen data stored in BigQuery. This program enables over 1,200
Using Google Cloud to serve 10,000s of personalized recs per second
In retail, it is personalize or die. Bluecore has a long history using BigQuery to generate and apply personalized recommendations. While this continues to work well in bulk, Google Cloud offers a variety of tools to enable real-time personalization.
Architecting a smart city on the cloud with SoftServe
In this episode of Stack Chat, Mark Mirchandani talks with Ronald Espinosa - Director of Intelligent Environments for SoftServe - about how their partnership with Google Cloud is enabling them to revamp the public sector. Specifically, they speak to
Adopting the cloud for the public sector with SoftServe
In this episode of Stack Chat, Mark Mirchandani talks with Ronald Espinosa - Director of Intelligent Environments for SoftServe - about how their partnership with Google Cloud is changing the way that the public sector works and operates. Ronald
Cloud-first Architecture for the public sector with SADA
In this episode of Stack Chat, Mark Mirchandani talks with Oleg Shalygin - Business Tech Lead for SADA Systems - about the architecture of Atom and how it leverages Google Cloud. Particularly, how Atom is using Google Kubernetes Engine for leveraging
GCP vs. Firebase - Functions & Firestore
In this episode we’ll explore two more products: Cloud Functions, and Cloud Firestore. Resources: Previous episode “GCP vs. Firebase - Projects & Storage” → https://goo.gle/2Si7MGL Firebase - https://goo.gle/2qZ1ORx Serverless Overview →
Migrating a Monolithic Application to Microservices (Cloud Next ‘19 UK)
Last year, Google Cloud’s Release Engineering team migrated two monolithic applications - each on a different tech stack in GCP - into dynamic microservices! For the first project, GlassPane, we used the Strangler Pattern to split a single App Engine
Platform Overview - Data & Storage
Hear Alexis Moussine-Pouchkine discuss the Platform Overview of Google Cloud Storage. Learn about data and storage essentials, such as BigQuery, CloudSQL, Cloud Dataproc, and much more! Google Cloud Codelabs → https://goo.gle/2XDECTW Google Cloud
Migrating a Monolithic Application to Microservices (Cloud Next '19)
Last year, Google Cloud’s Release Engineering team migrated a monolithic application into dynamic microservices. We leveraged Google Kubernetes Engine and Spring Cloud Kubernetes to make the migration seamless. In this talk, we will show you how we
Dev to Prod with Spring on GCP in 20 Minutes (Cloud Next '19)
This session shows how to create a new microservice using Java, Spring Boot that can create, retrieve, update, and delete data from Datastore, enhanced with production observability such as trace and correlated logging, and deployed to production
Driving a Realtime Personalization Engine With Cloud Bigtable (Cloud Next '19)
Segment builds customer data infrastructure. It helps thousands of companies collect, unify, and govern their first-party customer data from over 40 sources. A year ago, Segment faced a major engineering challenge. They were in the midst of launching
Cloud Bigtable performance 101
In this episode of Cloud Performance Atlas, Colt McAnlis talks about the performance of Bigtable, the technology behind the majority of Google products. Will we set enough places for performance? Stay tuned to find out! Recommendations on types of
Real-Time Stream Analytics with Google Cloud Dataflow: Common Use Cases & Patterns (Next Rewind '18)
Google Cloud Dataflow makes it easy to process and analyze real-time streaming data so that you can derive insights and react to new information in real-time. Learn how it is used in conjunction with other technologies, like PubSub, Kafka, BigQuery,