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RevenueBase delivers structured B2B data through Dynamic Data Feeds — continuously updated datasets on a monthly cadence. Data is available in our S3 bucket (we grant your AWS account access), or we share it through Snowflake Data Sharing to your Snowflake account. This guide walks you through onboarding, accessing your data, and understanding the tables available in your feed.

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Get access to your data feed

To get started, provide a few details based on your chosen delivery method. After you provide this information, RevenueBase will provision access and deliver your first dataset — typically within 1–2 business days.

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Provide your AWS details and get credentials

1

Provide your AWS Account ID

Share your 12-digit AWS Account ID with your RevenueBase onboarding contact. This is required so we can grant your account access to our S3 bucket.
You can find your AWS Account ID in the top-right dropdown of the AWS Console, or by running aws sts get-caller-identity in the AWS CLI.
2

Receive your access credentials

Once provisioned, we’ll share your bucket details including:
  • S3 bucket alias (or ARN-based access point)
  • AWS region for the bucket (by default eu-north-1)
Store your credentials securely. Do not commit them to version control or share them over unencrypted channels.
3

Verify access

Test your connection using the AWS CLI:
aws s3 ls s3://<your-bucket-alias>/<delivery_date>/  \
  --request-payer requester  \
  --region <target-bucket-region>
You can also access via ARN:
aws s3 ls s3://arn:aws:s3:<region>:<account-id>:accesspoint/<access-point-name>/<delivery_date>/  \
  --request-payer requester  \
  --region <target-bucket-region>
Use the AWS CLI — not the AWS Console web UI — to access RevenueBase buckets. The Console does not support --request-payer and will return access errors.

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Find your data in the bucket

RevenueBase supports dynamic feeds in three formats: CSV, JSON, and Parquet. When you get access to the data in S3, you get access to all three formats. For more on Parquet, see the official Parquet documentation. Your data lives in date-stamped folders within the S3 bucket. The path structure is:
<delivery_date>/<dataset_name>/<file_format>/
Path segmentDescription
delivery_dateDate of delivery in YYYYMMDD format (e.g., 20260201)
dataset_nameThe dataset included in your subscription (e.g., per, org, or a pre-joined dataset)
file_formatOne of json, csv, or parquet
Each monthly delivery creates a new folder. Previous deliveries remain accessible at their original paths and are never overwritten.
Data is split across multiple files within each delivery folder. This is by design — it enables parallel processing and significantly improves import performance for large datasets.
Azure and GCP delivery — Access and delivery through other clouds (Google Cloud Storage and Azure Blob Storage) is available. File format options (CSV, JSON, Parquet) and delivery cadence are the same as S3. Please contact your account manager or support@revenuebase.ai for details.

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Available tables

Your RevenueBase subscription includes access to the following tables, depending on your plan. In Snowflake, these appear under the RELEASES database. For S3 deliveries, each table corresponds to a dataset folder in your bucket. For full schema and field reference, see Contacts, Companies, Insight, and Historical experience.

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Person table (per)

The core contact-level table. Each row represents a person at a specific organization.
If someone holds multiple current positions, they will have multiple rows in the person table — each with a unique RBID_PAO but sharing the same RBID_PER.
RBID_ORG and RBID_PAO may be missing if the person’s LinkedIn profile does not link to a company page. This occurs because the company name field on LinkedIn is free text — people can enter anything and may skip linking to an existing company page.
Snowflake path: RELEASE.PER_LATEST S3 path: <delivery_date>/per/<format>/ See Person for the full field reference.

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Organization table (org)

Company-level data including firmographics, technographics, and company metadata. Snowflake path: RELEASE.ORG_LATEST S3 path: <delivery_date>/org/<format>/ See Companies for the full field reference.

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Insight table

Aggregated analytics and derived metrics across people and organizations. Snowflake path: RELEASE.INSIGHTS_LATEST See Insight for the full field reference.

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Raw feed

The unprocessed, full-fidelity data feed for advanced use cases and custom pipelines. Snowflake path: RELEASES.CUSTOM.RAW_FEED_PER_LATEST

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Pre-joined tables

Pre-joined tables combine multiple core tables so you can query people, companies, and optionally insights in a single view without writing joins. Pre-joined tables is an option your could choose for you subscription instead of separate tables of people/company/insights delivered to you. That way to data delivery less flexible, but easy to adopt and use.

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Person and Organization

Pre-joined table containing people and organization data in one view. Snowflake path: RELEASE.VELOCITY_BASE_UNLIMITED_LATEST S3 path: <delivery_date>/velocity_base_unlimited/<format>/

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Person, Organization, and Insight

Pre-joined table containing people, organization, and insight data in one view. Snowflake path: RELEASE.VELOCITY_ENHANCED_UNLIMITED_LATEST S3 path: <delivery_date>/velocity_enhanced_unlimited/<format>/

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Next steps

Data Freshness & Quality

How verification works, why records become stale, and quality assessment guidance.

FAQ

Answers to common questions about data organization, delivery, and troubleshooting.