Both Gong's API and Data Cloud allow you to access your Gong data for analytics purposes. Each solution has different attributes making them suitable for different use-case scenarios.

While the API includes additional functionality beyond analytics, it is possible to extract data via various API endpoints as well as from the Gong data cloud. This table describes the different points to consider if you are choosing between setting up the Gong data cloud and setting up an integration with the Calls and Stats APIs.

Attribute	Gong data cloud	Gong API
Data structure and analytics	Designed specifically for analytics with normalized tables Built-in soft delete mechanism to track deleted records Includes pre-built query templates ("cookbooks") for common use cases Data is immediately ready for analysis	Returns nested JSON data that typically requires transformation Requires additional ETL processing to prepare data for analysis More complex data structure that may need flattening for analytics use
Data freshness	Daily updates Appropriate for most analytical use cases where daily refreshes suffice	Near real-time data access Suitable for use cases requiring up-to-the-minute information
Implementation effort	Simple connection process Minimal technical expertise required No coding necessary Ready-to-use analytics-friendly format	Requires technical resources to implement Development time needed to write and maintain code Data must be adapted for analytics purposes
Storage and costs	Provides access to the complete data schema For reference, large enterprises with 5,000+ users and 6+ years of history typically use around 200GB of storage total Daily updates are typically a few hundred megabytes Snowflake integration is based on data sharing and there aren’t any storage costs. The other integrations are based on data copying and a small cost is included	Allows more granular control over what data is retrieved Storage requirements depend on implementation and retention choices
Data breadth or depth	Includes all data required to perform analytics in a BI tool Includes emails, meetings and more extensive usage data Analytics friendly data model	Provides extensive data on calls
Supported systems	Snowflake BigQuery Databricks

When to choose each solution

Use the Gong data cloud if:

Daily data updates meet your needs
You have limited technical resources or want to minimize technical implementation effort
You need comprehensive analytics capabilities out of the box for example:
- Activity reporting: Gong data cloud includes calls, emails and unrecorded meetings, which make activity reporting more accurate
- Gong usage: Gong data cloud includes a very detailed dataset for Gong usage. The API doesn’t expose the equivalent data.
- Productivity reports
- Competitor analysis, using a pre-built Gong cookbook.
You're starting fresh with Gong analytics integration

Use the API if:

You need more frequent than daily updates, for example Engage users who report on their team’s activities multiple times a day
You are an Engage user and you want reports on Engage flows, such as which prospects are assigned to which flows
You use an unsupported data warehouse platform
You're already integrated with the API and the information available is sufficient for your needs
You need specific data points not yet available in the Gong data cloud
You have use cases, such as audit logs, importing data to Gong, which can only be done via the API

Additional Considerations

Fivetran Users

If you use Fivetran to connect to Gong's API, note that while this provides an easier connection process, the same API limitations regarding data model and refresh rates still apply.

Security and Compliance

Each destination platform in Data Cloud has specific security protocols and considerations. For detailed security information about your specific data warehouse integration, refer to the documentation for your platform.

Data Visualization & BI