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Amazon DynamoDB to DuckDB integration — real-time, two-way sync

Keep Amazon DynamoDB and DuckDB 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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Why teams connect Amazon DynamoDB and DuckDB

Keep Amazon DynamoDB and DuckDB 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 Amazon DynamoDB and DuckDB 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 Backfill or migrate records into DynamoDB from another database using BatchWriteItem, then keep the two stores in continuous sync.
  • 02 Mirror a high-write DynamoDB table into a relational database so teams can join NoSQL application data against relational tables for reporting.
  • 03 Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.
  • 04 Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.

Common sync patterns

Shared reference data between services

Services that own separate databases stay consistent on the records they share, without a custom replication layer.

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 Amazon DynamoDB and DuckDB, so each workload runs on the engine that suits it.

What you can sync between Amazon DynamoDB and DuckDB

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 DynamoDB objects DuckDB objects How this pairing syncs
Tables Top-level containers, each with a partition key and optional sort key; Stacksync syncs a table as a stream of items with full read and write via PutItem, UpdateItem, and DeleteItem. Tables Columnar tables created via SQL; the destination for materialized sync data. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Global secondary indexes (GSIs) Alternate key projections that let you Query by non-key attributes without a full table Scan; read-only views maintained automatically by DynamoDB. Schemas Namespaces within a database used to organize tables in sync outputs. Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Schemas to DuckDB — each maps to any object or custom field on the other side.
Local secondary indexes (LSIs) Extra sort keys within the same partition key, defined at table creation; queried like the base table for alternate access patterns. Views SQL views used to shape or filter data for downstream consumers. Local secondary indexes (LSIs) is specific to Amazon DynamoDB and Views to DuckDB — each maps to any object or custom field on the other side.
DynamoDB Streams Ordered item-level change records (INSERT, MODIFY, REMOVE) with old/new image views and 24-hour retention; the native change-data-capture source Stacksync reads for near-real-time sync. External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. DynamoDB Streams is specific to Amazon DynamoDB and External files (Parquet/CSV/JSON) to DuckDB — each maps to any object or custom field on the other side.
Global Tables Multi-region, active-active replicas of a table kept in sync by DynamoDB; each region is read and written locally with last-writer-wins conflict resolution. Attached databases Additional database files or external systems attached into one session for cross-source queries. Global Tables is specific to Amazon DynamoDB and Attached databases to DuckDB — each maps to any object or custom field on the other side.
Time to Live (TTL) Per-item expiry timestamps; DynamoDB deletes expired items in the background and emits a Streams REMOVE record for each deletion. Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. Time to Live (TTL) is specific to Amazon DynamoDB and Database files to DuckDB — each maps to any object or custom field on the other side.

How changes propagate between Amazon DynamoDB and DuckDB

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 DynamoDB DuckDB Sub-second propagation

DetectionChanges in Amazon DynamoDB are captured at the source via change data capture — no polling loop against its API. DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views.

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

DuckDB Amazon DynamoDB 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 Amazon DynamoDB as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon DynamoDB: Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.
  • DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
What ships with Amazon DynamoDB ⇄ DuckDB

Connect Amazon DynamoDB and DuckDB for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon DynamoDB or DuckDB 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 DynamoDB or DuckDB record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon DynamoDB and DuckDB.

How the Amazon DynamoDB and DuckDB connectors work

Amazon DynamoDB

Integration surface
AWS SDK / low-level HTTPS JSON API at dynamodb.<region>.amazonaws.com (PutItem, GetItem, UpdateItem, DeleteItem, Query, Scan, BatchWriteItem, TransactWriteItems), plus PartiQL (ExecuteStatement) for SQL-style access and DynamoDB Streams for change capture.
Authentication
AWS Signature Version 4 (SigV4) signed requests using an IAM access key ID and secret key, or temporary STS credentials from an assumed IAM role; IAM policies scope access down to table and item level.
Change detection
DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views and 24-hour retention, read via shard iterators (or Kinesis Data Streams for longer retention). No native HTTP webhooks.
Capabilities
read · write · CDC
Rate limits
Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.

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
How it works

How to connect Amazon DynamoDB to DuckDB — 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 DynamoDB and DuckDB 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 DynamoDB connected
    DuckDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon DynamoDB and DuckDB 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 DynamoDB ⇄ DuckDB
    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 DynamoDB DuckDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon DynamoDB and DuckDB 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.

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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 480 integrations available for Amazon DynamoDB and DuckDB.

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