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Database ⇄ Data warehouse

Amazon Lightsail to BigQuery integration — real-time, two-way sync

Keep Amazon Lightsail and BigQuery 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 Lightsail and BigQuery

Connect Amazon Lightsail and BigQuery with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Amazon Lightsail's rows in BigQuery, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Amazon Lightsail where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Amazon Lightsail sync into BigQuery in real time, and result tables in BigQuery sync back into Amazon Lightsail, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • 02 Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • 03 Push cleaned or enriched records from central systems back into the Lightsail database behind a small web app.
  • 04 Migrate data continuously from a Lightsail database to a larger managed database as an application outgrows the VPS tier.

Common sync patterns

Operational data in the warehouse, minus the pipeline

Rows from Amazon Lightsail land in BigQuery as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in BigQuery sync into Amazon Lightsail, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

What you can sync between Amazon Lightsail and BigQuery

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 Lightsail objects BigQuery objects How this pairing syncs
Tables Relational tables read from and written to at row level. Tables The syncable unit: only tables can be synced per the Stacksync docs. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Users and Grants Database accounts used to give the sync connection scoped access. Clustered tables Supported; clustering is transparent to the sync. Users and Grants is specific to Amazon Lightsail and Clustered tables to BigQuery — each maps to any object or custom field on the other side.
Managed Databases Lightsail-hosted MySQL or PostgreSQL instances that a sync connects to as standard databases. Datasets Organizational container — you pick which dataset’s tables to sync. Managed Databases is specific to Amazon Lightsail and Datasets to BigQuery — each maps to any object or custom field on the other side.
Databases Logical databases on the instance that scope a connection. Projects Connection scope: the service account grants access per project. Databases is specific to Amazon Lightsail and Projects to BigQuery — each maps to any object or custom field on the other side.
Schemas Namespaces used when selecting tables to sync. Partitioned tables Synced like regular tables; partition columns map to target fields. Schemas is specific to Amazon Lightsail and Partitioned tables to BigQuery — each maps to any object or custom field on the other side.

How changes propagate between Amazon Lightsail and BigQuery

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 Lightsail BigQuery Interval-based propagation

DetectionStacksync polls Amazon Lightsail for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or key columns.

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

BigQuery Amazon Lightsail Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

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

Rate-limit considerations

  • Amazon Lightsail: No API-style rate limits; capacity is fixed by the chosen Lightsail bundle.
  • BigQuery: Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes.
What ships with Amazon Lightsail ⇄ BigQuery

Connect Amazon Lightsail and BigQuery for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Lightsail or BigQuery 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 Lightsail or BigQuery record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Lightsail and BigQuery.

How the Amazon Lightsail and BigQuery connectors work

Amazon Lightsail

Integration surface
MySQL or PostgreSQL wire protocol (SQL) to the managed database endpoint
Authentication
Database credentials; public endpoint access must be enabled or a tunnel used
Change detection
Polling on timestamp or key columns; log-based CDC depends on engine parameter access, which is more limited than on full RDS
Capabilities
read · write
Rate limits
No API-style rate limits; capacity is fixed by the chosen Lightsail bundle

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide
How it works

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

    Choose tables

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

Amazon Lightsail and BigQuery 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
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 473 integrations available for Amazon Lightsail and BigQuery.

Popular · 6 of 473
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