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Communications ⇄ Data warehouse

Amazon SES to BigQuery integration — real-time, two-way sync

Keep Amazon SES and BigQuery in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Amazon SES and BigQuery

Land the messages, calls, and events from Amazon SES in BigQuery as live tables, and write results back, without building or maintaining a pipeline.

Amazon SES produces a constant stream of activity — messages sent and received, calls placed and answered, meetings held, and the delivery and engagement events attached to them. That record is what the rest of the company wants to analyze, and it usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay to get it out.

Stacksync syncs Messages (SendEmail / SendBulkEmail), Contacts, Contact Lists, Email Templates from Amazon SES into tables in BigQuery in real time, handling schema, rate limits, and retries. Because the connection works in both directions, results computed in BigQuery — segments, contact updates, suppression flags — can be written back into fields in Amazon SES wherever it exposes them, so analysis lands where outreach actually happens.

Common use cases

  • 01 Keep Email Templates in sync from a CMS or Git-backed source into SES via CreateEmailTemplate and UpdateEmailTemplate across environments.
  • 02 Two-way sync Contacts and their topic subscription state between the SES contact list and a Postgres database or CRM so opt-outs propagate in both directions.
  • 03 Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
  • 04 Feed ML feature tables in BigQuery from operational systems on a continuous schedule

Common sync patterns

Communications analytics without ETL

Messages, calls, and events from Amazon SES arrive in BigQuery as queryable tables, current within seconds instead of a day behind.

Engagement and delivery on live data

Sends, opens, clicks, bounces, and call outcomes from Amazon SES land in BigQuery as they happen, so deliverability and response monitoring stop lagging the reality they describe.

Activity joined with everything else

Combine Amazon SES's activity with the CRM, product, and support data already in BigQuery to attribute outcomes to the touches that drove them, which no single tool can do alone.

What you can sync between Amazon SES and BigQuery

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Amazon SES objects BigQuery objects How this pairing syncs
Configuration Sets Named send-time rule groups that attach event destinations, IP pools, and suppression options; managed via Create/List ConfigurationSet operations. Partitioned tables Synced like regular tables; partition columns map to target fields. Configuration Sets is specific to Amazon SES and Partitioned tables to BigQuery — each maps to any object or custom field on the other side.
Sending Events Per-message send, delivery, bounce, complaint, open, and click events; not on any API, read from a configuration-set event destination (SNS/EventBridge/Firehose). Clustered tables Supported; clustering is transparent to the sync. Sending Events is specific to Amazon SES and Clustered tables to BigQuery — each maps to any object or custom field on the other side.
Messages (SendEmail / SendBulkEmail) Outbound email is produced via SendEmail and SendBulkEmail, accepting raw MIME or a template plus destination list. Send-only; there is no message store to read back. Datasets Organizational container — you pick which dataset’s tables to sync. Messages (SendEmail / SendBulkEmail) is specific to Amazon SES and Datasets to BigQuery — each maps to any object or custom field on the other side.
Contacts Subscribers in the contact list with per-topic opt-in state; CRUD via CreateContact/ListContacts/UpdateContact/DeleteContact, each carrying a LastUpdatedTimestamp for polling. Projects Connection scope: the service account grants access per project. Contacts is specific to Amazon SES and Projects to BigQuery — each maps to any object or custom field on the other side.
Contact Lists One list per AWS account, subdivided into Topics that group subscriptions; read and write via CreateContactList and GetContactList. Tables The syncable unit: only tables can be synced per the Stacksync docs. Contact Lists is specific to Amazon SES and Tables to BigQuery — each maps to any object or custom field on the other side.

How changes propagate between Amazon SES and BigQuery

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Amazon SES BigQuery Sub-second propagation

DetectionAmazon SES notifies Stacksync of record changes through webhook events. Message events (delivery, bounce, complaint, open, click) are pushed in near real time through configuration-set event destinations.

DeliveryEach detected change is applied to BigQuery as a row-level write, with types converted between the two schemas.

BigQuery Amazon SES Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

DeliveryEach detected change is written to Amazon SES through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Amazon SES: Every SES API action except SendEmail, SendRawEmail, and SendTemplatedEmail is throttled to 1 request/second per Region; the send rate and 24-hour sending quota are account-specific, adjustable, and per Region.
  • BigQuery: Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes.
What ships with Amazon SES ⇄ BigQuery

Connect Amazon SES and BigQuery for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon SES–BigQuery connection.

Real-time

Two-way sync

Changes in Amazon SES or BigQuery instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon SES or BigQuery data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Amazon SES or BigQuery record.

Observability

Monitoring

Track your Amazon SES ⇄ BigQuery sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon SES and BigQuery.

How the Amazon SES and BigQuery connectors work

Amazon SES

Integration surface
AWS SES API v2 (REST/JSON over HTTPS) plus an SMTP sending interface
Authentication
AWS IAM credentials (access key + secret) signed with Signature Version 4, or an assumed IAM role via STS; the SMTP interface uses SMTP credentials derived from an IAM user
Change detection
Message events (delivery, bounce, complaint, open, click) are pushed in near real time through configuration-set event destinations (SNS/EventBridge/Firehose); contacts, templates, and suppression entries are polled via List/Get operations
Capabilities
read · write · webhooks
Rate limits
Every SES API action except SendEmail, SendRawEmail, and SendTemplatedEmail is throttled to 1 request/second per Region; the send rate and 24-hour sending quota are account-specific, adjustable, and per Region

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide
How it works

How to connect Amazon SES to BigQuery — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Amazon SES and BigQuery with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Amazon SES connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon SES and BigQuery objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Amazon SES ⇄ BigQuery
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Amazon SES BigQuery
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon SES and BigQuery integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
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DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 446 integrations available for Amazon SES and BigQuery.

Popular · 8 of 446
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