Skip to content
Database ⇄ Business productivity

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

Keep Amazon DynamoDB and Google Sheets 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

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Amazon DynamoDB and Google Sheets

Mirror Google Sheets's data into Amazon DynamoDB so your own code can read and write it like any other table, with changes flowing both ways in seconds.

Engineers integrate with tools like Google Sheets through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Amazon DynamoDB.

Stacksync mirrors Sheets (tabs), Rows, Ranges, Named ranges from Google Sheets into Local secondary indexes (LSIs), DynamoDB Streams, Global Tables, Time to Live (TTL) in Amazon DynamoDB and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into Google Sheets, so the tool and the database never disagree.

Common use cases

  • 01 Publish pipeline, revenue, or inventory snapshots from a warehouse into a shared sheet for reporting.
  • 02 Use a sheet as a lightweight intake form whose rows become records in a production database.
  • 03 Use DynamoDB Streams as a change-data-capture source to push item INSERT, MODIFY, and REMOVE events into a CRM, search index, or operational database in near-real-time.
  • 04 Backfill or migrate records into DynamoDB from another database using BatchWriteItem, then keep the two stores in continuous sync.

Common sync patterns

Read Google Sheets with a query

Records from Google Sheets are ordinary rows in Amazon DynamoDB; join them, index them, and use them in application logic without touching the vendor API.

Automate Google Sheets from your codebase

Write to the synced tables in Amazon DynamoDB and Stacksync propagates the change into Google Sheets, replacing custom integration code.

React to changes as they happen

Updates in Google Sheets arrive as row changes in Amazon DynamoDB, so triggers, jobs, and services can respond in near real time.

What you can sync between Amazon DynamoDB and Google Sheets

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 Google Sheets objects How this pairing syncs
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. Sheets (tabs) Individual worksheets, typically mapped one-to-one to a synced table. DynamoDB Streams is specific to Amazon DynamoDB and Sheets (tabs) to Google Sheets — 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. Rows Treated as records; a header row usually defines field names. Global Tables is specific to Amazon DynamoDB and Rows to Google Sheets — 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. Ranges Addressed in A1 notation for batched reads and writes. Time to Live (TTL) is specific to Amazon DynamoDB and Ranges to Google Sheets — each maps to any object or custom field on the other side.
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. Named ranges Stable references that keep sync mappings valid when the grid moves. Tables is specific to Amazon DynamoDB and Named ranges to Google Sheets — each maps to any object or custom field on the other side.
Items Individual schemaless records (attributes up to 400 KB each); read with GetItem, Query, and Scan and written with PutItem or BatchWriteItem, so write is supported here. Cell values Untyped by default, so syncs handle type coercion for dates and numbers. Items is specific to Amazon DynamoDB and Cell values to Google Sheets — each maps to any object or custom field on the other side.
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. Spreadsheets The file-level container a sync connects to, identified by spreadsheet ID. Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Spreadsheets to Google Sheets — each maps to any object or custom field on the other side.

How changes propagate between Amazon DynamoDB and Google Sheets

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 Google Sheets 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 written to Google Sheets through its API, with automatic retries and rate-limit backoff.

Google Sheets Amazon DynamoDB Interval-based propagation

DetectionStacksync polls Google Sheets for changes on an incremental schedule, reading only records changed since the previous pass. Polling.

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.
  • Google Sheets: Subject to per-minute read and write quotas per project and per user, so large syncs are batched.
What ships with Amazon DynamoDB ⇄ Google Sheets

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon DynamoDB or Google Sheets 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 Google Sheets record.

Observability

Monitoring

Track your Amazon DynamoDB ⇄ Google Sheets 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 Google Sheets.

How the Amazon DynamoDB and Google Sheets 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.

Google Sheets

Integration surface
REST API (Google Sheets API), with file-level change signals available through the Drive API
Authentication
OAuth 2.0 (user consent) or Google service accounts
Change detection
Polling; the Sheets API has no cell-level webhooks, and Drive push notifications only signal file-level changes
Capabilities
read · write
Rate limits
Subject to per-minute read and write quotas per project and per user, so large syncs are batched.
How it works

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

    Choose tables

    Pick the Amazon DynamoDB and Google Sheets 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 ⇄ Google Sheets
    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 Google Sheets
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Amazon DynamoDB and Google Sheets 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
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
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 545 integrations available for Amazon DynamoDB and Google Sheets.

Popular · 8 of 545
All Amazon DynamoDB integrations All Google Sheets integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own