Datastore

Related topics

• Datastore is an alternative to Firestore From the official documentation: “As the successor to Datastore, Firestore is the recommended database for all new applications.”
• Apache Beam works with Datastore From the official documentation: “Apache Beam has many I/O connectors for several Google Cloud services, such as Bigtable, BigQuery, Datastore, Cloud SQL, and others.”
• BigQuery works with Datastore From the official documentation: “BigQuery lets you load [Datastore](/datastore) entities from a Cloud Storage bucket into a BigQuery table for analysis.”
• Cloud Storage works with Datastore From the official documentation: “Exports a copy of all or a subset of entities from Datastore to another storage system, such as Cloud Storage.”
• Datastore depends on Bigtable From the official documentation: “Datastore is built on top of Google's NoSQL database, [Bigtable](https://docs.cloud.google.com/bigtable), and is subject to Bigtable's performance characteristics.”
• Datastore is part of Firestore From the official documentation: “The `datastore.googleapis.com` service is bundled under the `firestore.googleapis.com` service.”
• Datastore works with Google Cloud CLI From the official documentation: “You can use the Google Cloud CLI to test your application locally and to manage indexes for your production Firestore in Datastore mode instance.”
• VPC Service Controls secures Datastore From the official documentation: “Firestore in Datastore mode supports VPC Service Controls but requires additional configuration to get full egress protection on import and export operations.”
• BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
• BigQuery works with Cloud Storage From the official documentation: “Sample to load Avro data from Cloud Storage into a new BigQuery table”
• BigQuery works with Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
• BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• Cloud SQL works with Cloud Storage From the official documentation: “Exports data from a Cloud SQL instance to a Cloud Storage bucket as a SQL dump or CSV file.”
• BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
• Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• BigQuery works with Bigtable From the official documentation: “BigQuery lets you query your Bigtable data from BigQuery.”
• Cloud SQL works with Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
• Cloud Storage works with Google Cloud CLI From the official documentation: “The gcloud CLI is the preferred command line tool for accessing Cloud Storage.”
• Apache Beam works with Dataflow From the official documentation: “This page explains how to run an Apache Beam pipeline on Dataflow with GPUs.”
• Cloud Logging works with Cloud SQL From the official documentation: “Database Migration Service and Cloud SQL use Cloud Logging.”
• Cloud Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
• Cloud Storage works with Compute Engine From the official documentation: “For example, you can create a service account that your Compute Engine instances use to access objects stored in Cloud Storage buckets.”
• Cloud Storage works with Managed Service for Apache Spark From the official documentation: “Managed Service for Apache Spark accesses these files on Cloud Storage.”
• Identity and Access Management secures Firestore From the official documentation: “This page describes the IAM permissions and roles for Firestore.”
• Apache Beam works with BigQuery From the official documentation: “Apache Beam has many I/O connectors for several Google Cloud services, such as Bigtable, BigQuery, Datastore, Cloud SQL, and others.”
• Bigtable works with Dataflow From the official documentation: “The Dataflow job then writes the transformed data to your Bigtable table.”
• Cloud Logging works with Compute Engine From the official documentation: “Compute Engine sends you Cloud Logging events for scheduled, started, or completed maintenance.”
• Compute Engine works with Google Cloud CLI From the official documentation: “Some applications might use commands from the gcloud CLI, which is included by default in most Compute Engine images.”
• Compute Engine works with Managed Service for Apache Spark From the official documentation: “Google Compute Engine provides a runtime environment for all features provided by Managed Service for Apache Spark and Gemini Enterprise Agent Platform.”
• Identity and Access Management secures Cloud Storage From the official documentation: “Cloud Storage uses Identity and Access Management (IAM) for authorization.”
• Managed Service for Apache Spark depends on Cloud Storage From the official documentation: “Managed Service for Apache Spark uses Cloud Storage as its default distributed file system.”
• VPC Service Controls secures Cloud Storage From the official documentation: “Storage Transfer Service supports transfers to Cloud Storage buckets protected by VPC Service Controls.”
• Apache Beam works with Bigtable From the official documentation: “Write data to Cloud Bigtable with Apache Beam.”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
• BigQuery works with Managed Service for Apache Spark From the official documentation: “This means you can quickly read and write BigQuery data to and from Managed Service for Apache Spark.”
• Bigtable is an alternative to Cloud Storage From the official documentation: “If the joining data is in the gigabyte or terabyte range, use either Bigtable or Cloud Storage to merge the joining data to the driving data, depending on the nature of the data.”
• Bigtable works with Managed Service for Apache Spark From the official documentation: “With Managed Service for Apache Spark, you can run Hadoop jobs that read from and write to Bigtable.”
• Cloud Logging is an alternative to Cloud Storage From the official documentation: “Instead, they are routed to either Cloud Storage (recommended) or Cloud Logging, depending on your organization's configuration.”
• Dataflow depends on Apache Beam From the official documentation: “Dataflow is based on the open-source Apache Beam project.”
• Dataflow depends on Cloud Storage From the official documentation: “Begin by creating a Cloud Storage bucket using the Google Cloud console or Google Cloud CLI. The Dataflow pipeline uses this bucket as a temporary storage location.”
• Dataflow depends on Compute Engine From the official documentation: “When Dataflow runs a pipeline, the processing is distributed across multiple Compute Engine virtual machines (VMs), also known as workers.”
• Dataflow works with Google Cloud CLI From the official documentation: “Dataflow integrates with the Google Cloud CLI.”
• Dataflow is an alternative to Managed Service for Apache Spark From the official documentation: “For more complex data loads into your Cloud SQL for PostgreSQL database, consider using Dataflow or Managed Service for Apache Spark, which involves creating an ETL process.”
• Firestore works with VPC Service Controls From the official documentation: “Because Firestore with MongoDB compatibility is compliant with VPC Service Controls, you can use this domain in VPC Service Controls scenarios.”
• Identity and Access Management secures Compute Engine From the official documentation: “Compute Engine uses Identity and Access Management (IAM) for authorization.”
• Identity and Access Management works with VPC Service Controls From the official documentation: “VPC Service Controls perimeters and Identity and Access Management (IAM) roles work together.”
• Managed Service for Apache Spark depends on Compute Engine From the official documentation: “Managed Service for Apache Spark clusters are built on [Compute Engine](/compute) instances.”
• VPC Service Controls secures Compute Engine From the official documentation: “To further protect your Compute Engine resources, you can protect them using [VPC Service Controls](/vpc-service-controls/docs/overview).”
• Apache Beam works with Cloud SQL From the official documentation: “Apache Beam has many I/O connectors for several Google Cloud services, such as Bigtable, BigQuery, Datastore, Cloud SQL, and others.”
• BigQuery depends on Cloud Storage From the official documentation: “BigQuery relies on Cloud Storage for staging file data and supports reading from and writing to several other sources and Google Cloud services.”
• BigQuery works with Compute Engine From the official documentation: “Compute Engine integrates with Google Cloud technologies such as Cloud Storage, Google Kubernetes Engine, and BigQuery, to extend beyond the basic computational capability to create more complex and sophisticated applications.”
• BigQuery is an alternative to Managed Service for Apache Spark From the official documentation: “An Analytics Workload refers to the migration of new Data Lake and Data Warehouse environments from on-premises (e.g., Teradata, Cloudera) and cloud platforms (e.g., Snowflake, Redshift, Databricks) to BigQuery or Managed Service for Apache Spark on Google Cloud.”
• BigQuery works with VPC Service Controls From the official documentation: “BigQuery integrates with VPC Service Controls to restrict access to your BigQuery resources from specific networks.”
• Bigtable is an alternative to Cloud SQL From the official documentation: “If you're interested in evaluating how the performance of your on-premises databases compares to [Cloud SQL](/sql), [Spanner](/spanner), [Firestore](/firestore), or [Bigtable](/bigtable), you could implement a PoC where the same business logic uses different databases.”
• Bigtable works with Cloud Storage From the official documentation: “For example, if you frequently write data to Bigtable from a Cloud Storage bucket in the `us-central1` (Iowa) region, create your Bigtable cluster in a zone within `us-central1`.”
• Bigtable works with Compute Engine From the official documentation: “OAuth scopes let Google Cloud services such as Compute Engine and Dataflow authenticate and connect to Bigtable.”
• Bigtable works with Google Cloud CLI From the official documentation: “When you use the [gcloud CLI](/sdk/gcloud/reference/bigtable) to access Bigtable, you authenticate to Google Cloud as a principal, which provides the credentials used by the gcloud CLI commands.”
• Cloud Logging works with Dataflow From the official documentation: “You can control the volume of Dataflow logs ingested by Cloud Logging by following the [Filter logs documentation](/dataflow/docs/guides/filter-logs).”