Real-time
Two-way sync
Changes in DuckDB or Dynamo DB instantly reflect in both systems. No stale data, no manual imports.
Database
DuckDB to Dynamo DB integration — real-time, two-way sync
Keep DuckDB and Dynamo DB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from MuleSoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect DuckDB and Dynamo DB
Keep DuckDB and Dynamo DB synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between DuckDB and Dynamo DB continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Sync SaaS data to Parquet on object storage and query it with DuckDB without standing up a warehouse.
- 02 Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.
- 03 Stream item changes from DynamoDB application tables into a Postgres or warehouse copy for SQL analytics.
- 04 Sync customer records between DynamoDB-backed services and a CRM so support and sales see live application state.
Common sync patterns
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both DuckDB and Dynamo DB, so each workload runs on the engine that suits it.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
What you can sync between DuckDB and Dynamo DB
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.
| DuckDB objects | Dynamo DB objects | How this pairing syncs | |
|---|---|---|---|
| Tables Columnar tables created via SQL; the destination for materialized sync data. | Tables The top-level containers a sync targets; each table is addressed independently. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Attributes Per-item fields, including nested maps and lists, flattened or mapped during sync. | External files (Parquet/CSV/JSON) is specific to DuckDB and Attributes to Dynamo DB — each maps to any object or custom field on the other side. | |
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Partition and Sort Keys The primary key pair used as the match key for bi-directional sync. | Attached databases is specific to DuckDB and Partition and Sort Keys to Dynamo DB — each maps to any object or custom field on the other side. | |
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Global Secondary Indexes Alternate access paths used when sync queries filter on non-key attributes. | Database files is specific to DuckDB and Global Secondary Indexes to Dynamo DB — each maps to any object or custom field on the other side. | |
| Schemas Namespaces within a database used to organize tables in sync outputs. | DynamoDB Streams Ordered item-level change records consumed for incremental sync. | Schemas is specific to DuckDB and DynamoDB Streams to Dynamo DB — each maps to any object or custom field on the other side. | |
| Views SQL views used to shape or filter data for downstream consumers. | Global Tables Multi-region replicas relevant when syncs must read from a specific region. | Views is specific to DuckDB and Global Tables to Dynamo DB — each maps to any object or custom field on the other side. |
How changes propagate between DuckDB and Dynamo DB
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.
DuckDB Dynamo DB Interval-based propagation
DetectionStacksync polls DuckDB for changes on an incremental schedule, reading only records changed since the previous pass. Polling or full re-reads.
DeliveryEach detected change is applied to Dynamo DB as a row-level write, with types converted between the two schemas.
Dynamo DB DuckDB Sub-second propagation
DetectionChanges in Dynamo DB are captured at the source via change data capture — no polling loop against its API. Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration.
DeliveryEach detected change is applied to DuckDB as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
- Dynamo DB: Throughput is governed by the table's provisioned or on-demand capacity mode.
What ships with DuckDB ⇄ Dynamo DB
Connect DuckDB and Dynamo DB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–Dynamo DB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever DuckDB or Dynamo DB 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 DuckDB or Dynamo DB record.
Observability
Monitoring
Track your DuckDB ⇄ Dynamo DB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between DuckDB and Dynamo DB.
How the DuckDB and Dynamo DB connectors work
DuckDB
- Integration surface
- In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
- Authentication
- None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
- Change detection
- Polling or full re-reads; no change feed or transaction log API
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by local compute and I/O
Dynamo DB
- Integration surface
- Proprietary JSON-over-HTTPS API accessed through AWS SDKs; PartiQL supported for SQL-like queries
- Authentication
- AWS IAM credentials with SigV4 request signing
- Change detection
- Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration
- Capabilities
- read · write · CDC
- Rate limits
- Throughput is governed by the table's provisioned or on-demand capacity mode
How it works
How to connect DuckDB to Dynamo DB — 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.
- 01
Connect your apps
Authenticate DuckDB and Dynamo DB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
DuckDB
connected
Dynamo DB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the DuckDB and Dynamo DB 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.
objects · DuckDB ⇄ Dynamo DBCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
DuckDB Dynamo DBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
DuckDB and Dynamo DB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between DuckDB and Dynamo DB: authenticate both systems, choose the objects to sync (such as DuckDB's Tables and External files (Parquet/CSV/JSON)), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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.
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Common patterns for DuckDB and Dynamo DB: Regional or environment copies; Cross-engine sync; Migration with zero-downtime cutover. Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
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DuckDB: In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default. Authentication: None built in; access control is file-system level (MotherDuck adds token auth for its hosted service). Dynamo DB: Proprietary JSON-over-HTTPS API accessed through AWS SDKs; PartiQL supported for SQL-like queries. Authentication: AWS IAM credentials with SigV4 request signing. Stacksync manages authentication, retries, and rate limits on both sides.
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DuckDB: Concurrency is single-writer: one process holds write access to a database file at a time, which shapes how sync jobs schedule writes. Dynamo DB: PartiQL provides a SQL-compatible query layer over the same key-based access model. Stacksync's field mapping accounts for these differences between DuckDB and Dynamo DB without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means DuckDB and Dynamo DB records are not retained after a sync operation.
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 392 integrations available for DuckDB and Dynamo DB.
Popular · 5 of 392
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DuckDB ⇄ IBM Informix -
DuckDB ⇄ InfluxDB -
DuckDB ⇄ InterSystems IRIS -
Dynamo DB ⇄ MarkLogic -
Dynamo DB ⇄ Neo4j
No integrations match .
