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

Keep Amazon DynamoDB and Google Cloud Spanner 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 DynamoDB and Google Cloud Spanner

Keep Amazon DynamoDB and Google Cloud Spanner 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 Google Cloud Spanner 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 Consolidate data from a globally distributed Spanner deployment into regional business systems.
  • 04 Push billing or entitlement changes from finance tools into Spanner tables the application reads at runtime.

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 Amazon DynamoDB and Google Cloud Spanner, 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 Amazon DynamoDB and Google Cloud Spanner

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 Cloud Spanner 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 Relational tables mapped one-to-one to sync targets. 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. Databases Top-level containers that scope schema and sync configuration. Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Databases to Google Cloud Spanner — 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. Rows The unit of read and write in each sync cycle, keyed by primary key. Local secondary indexes (LSIs) is specific to Amazon DynamoDB and Rows to Google Cloud Spanner — 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. Interleaved tables Child rows physically co-located with parents; synced as related records. DynamoDB Streams is specific to Amazon DynamoDB and Interleaved tables to Google Cloud Spanner — 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. Secondary indexes Used to make incremental read queries efficient on non-key columns. Global Tables is specific to Amazon DynamoDB and Secondary indexes to Google Cloud Spanner — 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. Change streams Capture inserts, updates, and deletes for log-style change data capture. Time to Live (TTL) is specific to Amazon DynamoDB and Change streams to Google Cloud Spanner — each maps to any object or custom field on the other side.

How changes propagate between Amazon DynamoDB and Google Cloud Spanner

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 Cloud Spanner 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 Google Cloud Spanner as a row-level write, with types converted between the two schemas.

Google Cloud Spanner Amazon DynamoDB Sub-second propagation

DetectionChanges in Google Cloud Spanner are captured at the source via change data capture — no polling loop against its API. Change streams (log-style CDC), or timestamp-based polling queries.

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 Cloud Spanner: Throughput is bounded by the instance's provisioned compute capacity rather than a fixed API quota.
What ships with Amazon DynamoDB ⇄ Google Cloud Spanner

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

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

Real-time

Two-way sync

Changes in Amazon DynamoDB or Google Cloud Spanner 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 Cloud Spanner 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 Cloud Spanner record.

Observability

Monitoring

Track your Amazon DynamoDB ⇄ Google Cloud Spanner 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 Cloud Spanner.

How the Amazon DynamoDB and Google Cloud Spanner 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 Cloud Spanner

Integration surface
gRPC/REST client API with SQL query surface (GoogleSQL and PostgreSQL-interface dialects)
Authentication
Google Cloud IAM (service accounts)
Change detection
Change streams (log-style CDC), or timestamp-based polling queries
Capabilities
read · write · CDC
Rate limits
Throughput is bounded by the instance's provisioned compute capacity rather than a fixed API quota.
How it works

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

    Choose tables

    Pick the Amazon DynamoDB and Google Cloud Spanner 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 Cloud Spanner
    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 Cloud Spanner
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Amazon DynamoDB and Google Cloud Spanner 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.

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:

Related integrations

Every pair below is a real-time, two-way sync. Search all 459 integrations available for Amazon DynamoDB and Google Cloud Spanner.

Popular · 5 of 459
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