Seller delivery data feeds service - AWS Marketplace

Seller delivery data feeds service

AWS Marketplace provides data feeds as a mechanism to send structured, up-to-date product and customer information from AWS Marketplace systems to seller Amazon S3 buckets for ETL (extract, transform, and load) between seller-owned business intelligence tools.

The transactional data is delivered and appended in a bi-temporal structure so sellers can store and query data along two timelines with timestamps for both

  • valid time: when a fact occurred in the real world (“what you knew”)

  • system time: when that fact was recorded to the database (“when you knew it”).

Data feeds are delivered daily at 4pm PST (midnight UTC) following an update from the prior day containing 24 hours of data from the previous day. An update can be defined by a customer subscribing, a customer being invoiced, or AWS disbursing payment.

This section provides an overview of data feeds and explains how to access and use them. Subsequent sections describe each data feed.

Storage and structure of data feeds

Data feeds collect and deliver comma-separated value (CSV) files to an encrypted Amazon S3 bucket that you provide. The CSV files have the following characteristics:

  • They follow 4180 standards.

  • Character encoding is UTF-8 without BOM.

  • Commas are used as separators between values.

  • Fields are escaped by double quotation marks.

  • \n is the line feed character.

  • Dates are reported in the UTC time zone, are in ISO 8601 date and time format, and are accurate within 1 second.

  • All *_period_start_date and *_period_end_date values are inclusive, which means that 23:59:59 is the last possible timestamp for any day.

  • All monetary fields are preceded with a currency field.

  • Monetary fields use a period (.) character as a decimal separator, and don't use a comma (,) as a thousands separator.

Data feeds are generated and stored as follows:

  • Data feeds are generated within a day, and contain 24 hours of data from the previous day.

  • In the Amazon S3 bucket, data feeds are organized by month using the following format:


  • As each daily data feed is generated, it is appended to the existing CSV file for that month. When a new month starts, a new CSV file is generated for each data feed.

  • Information in data feeds is backfilled from 2010/01/01 to 2020/04/30 (inclusive) and is available in the CSV file in the year=2010/month=01 subfolder.

    You may notice cases where the current month's file for a given data feed contains only column headers, and no data. This means that there were no new entries for that month for the feed. This can happen with data feeds that are updated less frequently, like the product feed. In these cases, data is available in the backfilled folder.

  • In Amazon S3, you can create an Amazon S3 lifecycle policy to manage how long to keep files in the bucket.

  • You can configure Amazon SNS to notify you when data is delivered to your encrypted S3 bucket. For information on how to configure notifications, see Getting started with Amazon SNS in the Amazon Simple Notification Service Developer Guide.

Historization of the data

Each data feed includes columns that document the history of the data. Except for valid_to, these columns are common to all data feeds. They're included as a common history schema and are useful in querying the data.

Column name Description
valid_from The first date that the value for the primary key is valid for in relation to values for other fields.
valid_to This column is only shown on the Address data feed and is always blank.
insert_date The date a record was inserted into the data feed.
update_date The date the record was last updated.
delete_date This column is always blank.

The following shows an example of these columns.

valid_from valid_to insert_date update_date delete_date
2018-12-12T02:00:00Z 2018-12-12T02:00:00Z 2018-12-12T02:00:00Z
2019-03-29T03:00:00Z 2019-03-29T03:00:00Z 2019-03-29T03:00:00Z
2019-03-29T03:00:00Z 2019-03-29T03:00:00Z 2019-04-28T03:00:00Z

The valid_from and update_date field together form a bi-temporal data model. The valid_from field, as it is named, tells you when the item is valid from. If the item was edited, it can have multiple records in the feed, each with a different update_date, but the same valid_from date. For example, to find the current value for an item, you would find the record with the most recent update_date, from the list of records with the most recent valid_from date.

In the example above, the record was originally created 2018-12-12. It was then changed on 2019-03-29 (for example, if the address in the record changed). Later, on 2019-04-28, the address change was corrected (so the valid_from didn't change, but the update_date did). Correcting the address (a rare event) retroactively changes the record from the original valid_from date, so that field didn't change. A query to find the most recent valid_from would return two records, the one with the latest update_date gives you the actual current record.

Accessing data feeds

To access data feeds, you need to configure your environment to receive data feeds to an encrypted Amazon S3 bucket. AWS Marketplace provides an AWS CloudFormation template that you can use to simplify configuration.

To use the AWS CloudFormation template to configure your environment to receive data feeds
  1. Open a web browser and sign into the AWS Marketplace Management Portal, then go to Set up customer data storage.

  2. Choose Create resources with AWS CloudFormation template to open the template in the AWS CloudFormation console in another window.

  3. In the template, specify the following and then choose Next:

    • Stack name – The collection of resources you're creating to enable access to data feeds.

    • Amazon S3 bucket name – The bucket for storing data feeds.

    • (Optional) Amazon SNS topic name – The topic for receiving notifications when AWS delivers new data to the Amazon S3 bucket.

  4. On the Review page, confirm your entries and choose Create stack. This will open a new page with the CloudFormation status and details.

  5. From the Resources tab, copy Amazon Resource Names (ARNs) for the following resources from the CloudFormation page into the fields on the AWS Marketplace Set up customer data storage page:

    • Amazon S3 bucket for storing data feeds

    • AWS KMS key for encrypting the Amazon S3 bucket

    • (Optional) Amazon SNS topic for receiving notifications when AWS delivers new data to the Amazon S3 bucket

  6. On the Set up customer data storage page, choose Submit.

  7. (Optional) Edit the policies created by the CloudFormation template. See Data feed policies for more details.

You are now subscribed to data feeds. The next time data feeds are generated, you can access the data.

For more information about AWS CloudFormation templates, see Working with AWS CloudFormation templates in the AWS CloudFormation User Guide.

Data feed policies

When your Amazon S3 bucket is created by the CloudFormation template, it will create policies for access attached to that bucket, the AWS KMS key, and the Amazon SNS topic. The policies allow the AWS Marketplace reports service to write to your bucket and SNS topic with the data feed information. Each policy will have a section like the following (this example is from the Amazon S3 bucket).

{ "Sid": "AwsMarketplaceDataFeedsAccess", "Effect": "Allow", "Principal": { "Service": "" }, "Action": [ "s3:ListBucket", "s3:GetObject", "s3:PutObject", "s3:GetEncryptionConfiguration", "s3:GetBucketAcl", "s3:PutObjectAcl" ], "Resource": [ "arn:aws:s3:::datafeed-bucket", "arn:aws:s3:::datafeed-bucket/*" ] },

In this policy, is the service principal that AWS Marketplace uses to push data to the Amazon S3 bucket. The datafeed-bucket is the bucket that you specified in the CloudFormation template.

When the AWS Marketplace reports service calls Amazon S3, AWS KMS, or Amazon SNS, it will provide the ARN of the data it is intending to write to the bucket when it does. To ensure that the only data written to your bucket is data written on your behalf, you can specify the aws:SourceArn in the condition of the policy. In the following example, you must replace the account-id with the ID for your AWS account.

{ "Sid": "AwsMarketplaceDataFeedsAccess", "Effect": "Allow", "Principal": { "Service": "" }, "Action": [ "s3:ListBucket", "s3:GetObject", "s3:PutObject", "s3:GetEncryptionConfiguration", "s3:GetBucketAcl", "s3:PutObjectAcl" ], "Resource": [ "arn:aws:s3:::datafeed-test-bucket", "arn:aws:s3:::datafeed-test-bucket/*" , "Condition": { "StringEquals": { "aws:SourceAccount": "account-id", "aws:SourceArn": ["arn:aws:marketplace::account-id:AWSMarketplace/SellerDataSubscription/DataFeeds_V1", "arn:aws:marketplace::account-id:AWSMarketplace/SellerDataSubscription/Example-Report"] } } },

Unsubscribing from data feeds

Open a web browser and sign in to the AWS Marketplace Management Portal. Then, go to the Contact us page to submit an unsubscribe request to the AWS Marketplace Seller Operations team. The unsubscribe request can take up to 10 business days to process.

Using data feeds

When data is available in your Amazon S3 bucket, you can use data feeds in the following ways:

  • Download the .CSV files from the Amazon S3 bucket you created in Accessing data feeds so that you can view the data in a spreadsheet.

  • Use ETL (extract, transform, and load), SQL query, business analytics tools to collect and analyze the data.

    You can use AWS services to collect and analyze data, or any third-party tool that can perform analysis of .CSV-based datasets.

Example: Use AWS services to collect and analyze data

The following procedure assumes that you've already configured your environment to receive data feeds to an Amazon S3 bucket and that the bucket contains data feeds.

To collect and analyze data from data feeds
  1. From the AWS Glue console, create a crawler to connect to the Amazon S3 bucket that stores the data feeds, extract the data you want, and create metadata tables in the AWS Glue Data Catalog.

    For more information about AWS Glue, see the AWS Glue Developer Guide.

  2. From the Athena console, run SQL queries on the data in the AWS Glue Data Catalog.

    For more information about Athena see the Amazon Athena User Guide.

  3. From the Amazon QuickSight console, create an analysis and then create a visual of the data.

    For more information about Amazon QuickSight, see the Amazon QuickSight User Guide.

For a detailed example of one way to use AWS services to collect and analyze data in data feeds, see Using Seller Data Feed Delivery Service, Amazon Athena, and Amazon QuickSight to create seller reports at the AWS Marketplace Blog.