Nylas connector
Set up the Nylas connector in Kaivo: authentication, configuration, the 12 BigQuery tables it syncs, and answers to common questions.
Written By Lauri Raivio
Last updated 16 days ago
Kaivo is a fully managed data platform that syncs your Nylas data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your survey and email data instead of moving it.
What is the Nylas connector
Sync your Nylas communications data into BigQuery with Kaivo to analyse email, calendar, and contact activity.
Getting started with the Nylas connector
- Sign up for Kaivo and create a workspace.
- Connect your Nylas account.
- Choose which tables to sync.
- Wait for the initial sync to finish.
- Query your data in BigQuery or your favourite AI or BI tool.
Authenticating Nylas
Authenticate with your API Key.
Configuring the Nylas connector
When you set up the connector, you provide:
Tables and columns synced from Nylas
Kaivo syncs 12 tables from Nylas into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
calendars (13 columns)
calendars (13 columns)
connectors (9 columns)
connectors (9 columns)
Subtable: connectors__scope
contact_groups (8 columns)
contact_groups (8 columns)
contacts (14 columns)
contacts (14 columns)
Subtable: contacts__emails
Subtable: contacts__groups
Subtable: contacts__im_addresses
Subtable: contacts__phone_numbers
Subtable: contacts__physical_addresses
Subtable: contacts__web_pages
credentials (3 columns)
credentials (3 columns)
Subtable: credentials__data
drafts (12 columns)
drafts (12 columns)
Subtable: drafts__attachments
Subtable: drafts__bcc
Subtable: drafts__cc
Subtable: drafts__folders
Subtable: drafts__from
Subtable: drafts__reply_to
Subtable: drafts__to
events (39 columns)
events (39 columns)
Subtable: events__conferencing__details__phone
Subtable: events__participants
Subtable: events__reminders__overrides
Subtable: events__resources
folders (8 columns)
folders (8 columns)
Subtable: folders__attributes
grants (11 columns)
grants (11 columns)
Subtable: grants__scope
messages (12 columns)
messages (12 columns)
Subtable: messages__attachments
Subtable: messages__bcc
Subtable: messages__cc
Subtable: messages__folders
Subtable: messages__from
Subtable: messages__reply_to
Subtable: messages__to
scheduled_messages (7 columns)
scheduled_messages (7 columns)
threads (24 columns)
threads (24 columns)
Subtable: threads__draft_ids
Subtable: threads__folders
Subtable: threads__latest_draft_or_message__attachments
Subtable: threads__latest_draft_or_message__bcc
Subtable: threads__latest_draft_or_message__cc
Subtable: threads__latest_draft_or_message__folders
Subtable: threads__latest_draft_or_message__from
Subtable: threads__latest_draft_or_message__reply_to
Subtable: threads__latest_draft_or_message__to
Subtable: threads__message_ids
Subtable: threads__participants
How the Nylas sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Nylas supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.
Frequently asked questions
How long does the initial sync take for Nylas?
It depends on how much history is in your Nylas account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.
Can I sync only some tables or columns?
Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.
What happens when Nylas's schema changes?
New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in Nylas, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.
How do I handle GDPR or data deletion requests?
Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in Nylas instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the Nylas connector in Kaivo and all of its synced data is deleted with it.
Common use cases for Nylas data
Email and calendar activity
Use messages and events to track communication and meeting volume over time.
Contact view
Join contacts with messages to understand who you communicate with.
Scheduling
Use scheduled_messages and threads to follow outreach and conversations.
Use Nylas data in your AI and BI tools
Once Nylas data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with Nylas data.
Claude
Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →
Power BI
Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →
Data Studio
Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →
Tableau
The premium analytics standard, with native BigQuery integration. Setup guide →
Google Sheets
Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →
Excel
Connect via Power Query's BigQuery connector. Setup guide →
Metabase
Open-source BI tool with strong BigQuery support. Setup guide →
See our pricing page for Nylas connector pricing and plan details.
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