Two-way sync
Changes in Amazon SES or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon SES and Cloudera Data Platform in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 Cloudera Data Platform in real time, handling schema, rate limits, and retries. Because the connection works in both directions, results computed in Cloudera Data Platform — 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.
Messages, calls, and events from Amazon SES arrive in Cloudera Data Platform as queryable tables, current within seconds instead of a day behind.
Sends, opens, clicks, bounces, and call outcomes from Amazon SES land in Cloudera Data Platform as they happen, so deliverability and response monitoring stop lagging the reality they describe.
Combine Amazon SES's activity with the CRM, product, and support data already in Cloudera Data Platform to attribute outcomes to the touches that drove them, which no single tool can do alone.
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 | Cloudera Data Platform objects | How this pairing syncs | |
|---|---|---|---|
| Suppression List Addresses auto-added on bounce or complaint; read with ListSuppressedDestinations and written with Put/DeleteSuppressedDestination to control re-sends. | Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | Suppression List is specific to Amazon SES and Partitions to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Verified Identities Email-address and domain identities cleared to send; managed via CreateEmailIdentity, ListEmailIdentities, GetEmailIdentity (DKIM and verification status). | Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. | Verified Identities is specific to Amazon SES and Object store / HDFS files to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Configuration Sets Named send-time rule groups that attach event destinations, IP pools, and suppression options; managed via Create/List ConfigurationSet operations. | Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Configuration Sets is specific to Amazon SES and Databases to Cloudera Data Platform — 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). | Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | Sending Events is specific to Amazon SES and Hive tables to Cloudera Data Platform — 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. | Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Messages (SendEmail / SendBulkEmail) is specific to Amazon SES and Impala tables to Cloudera Data Platform — 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. | Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | Contacts is specific to Amazon SES and Kudu tables to Cloudera Data Platform — each maps to any object or custom field on the other side. |
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.
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 Cloudera Data Platform as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Cloudera Data Platform for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL on timestamp or partition columns.
DeliveryEach detected change is written to Amazon SES through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon SES–Cloudera Data Platform connection.
Changes in Amazon SES or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon SES or Cloudera Data Platform data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon SES or Cloudera Data Platform record.
Track your Amazon SES ⇄ Cloudera Data Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon SES and Cloudera Data Platform.
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.
Authenticate Amazon SES and Cloudera Data Platform with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Amazon SES and Cloudera Data Platform 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Amazon SES and Cloudera Data Platform: authenticate both systems, choose the objects to sync (such as Amazon SES's Suppression List and Verified Identities), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Amazon SES and Cloudera Data Platform. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Amazon SES: 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. On Cloudera Data Platform: Polling via SQL on timestamp or partition columns; no consumer-facing change feed. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Amazon SES side: Messages (SendEmail / SendBulkEmail), Contacts, Contact Lists, Email Templates, plus custom fields where Amazon SES exposes them. On the Cloudera Data Platform side: Kudu tables, Iceberg tables, Views, Partitions. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Amazon SES and Cloudera Data Platform: Communications analytics without ETL; Engagement and delivery on live data; Activity joined with everything else. Messages, calls, and events from Amazon SES arrive in Cloudera Data Platform as queryable tables, current within seconds instead of a day behind.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 340 integrations available for Amazon SES and Cloudera Data Platform.