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Database ⇄ Business productivity

Amazon Aurora to Aviato integration — real-time data sync

Keep Amazon Aurora and Aviato 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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Why teams connect Amazon Aurora and Aviato

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

Aviato is a read-only source: Stacksync reads its data in real time and delivers it into Amazon Aurora, so Amazon Aurora always reflects the current state of Aviato — without exports, scripts, or schedulers.

Engineers integrate with tools like Aviato 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 Aurora.

Stacksync mirrors Funding Round, Investor, Headcount Snapshot, Employment Record from Aviato into Tables, Views, Materialized Views, Columns and Data Types in Amazon Aurora 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 Aviato, so the tool and the database never disagree.

Common use cases

  • 01 Feed lead-scoring models with growth signals (funding recency, headcount trajectory) pulled from Aviato
  • 02 Backfill missing firmographic fields on inbound leads by matching them to Aviato company profiles
  • 03 Stream row-level changes from Aurora into a warehouse for near-real-time analytics without batch exports.
  • 04 Consolidate several Aurora clusters into one reporting database.

Common sync patterns

Automate Aviato from your codebase

Write to the synced tables in Amazon Aurora and Stacksync propagates the change into Aviato, replacing custom integration code.

React to changes as they happen

Updates in Aviato arrive as row changes in Amazon Aurora, so triggers, jobs, and services can respond in near real time.

One integration pattern for the whole stack

Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.

What you can sync between Amazon Aurora and Aviato

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 Aurora objects Aviato objects How this pairing syncs
Tables Relational tables synced bi-directionally at row level. Headcount Snapshot Point-in-time employee counts used to track company growth over time Tables is specific to Amazon Aurora and Headcount Snapshot to Aviato — each maps to any object or custom field on the other side.
Views Read-only query-backed sources for downstream syncs. Employment Record Person-to-company links with role and tenure that model team movement Views is specific to Amazon Aurora and Employment Record to Aviato — each maps to any object or custom field on the other side.
Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. Acquisition / Exit Event M&A and exit records tied to the acquired company profile Materialized Views is specific to Amazon Aurora and Acquisition / Exit Event to Aviato — each maps to any object or custom field on the other side.
Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. Company Private-company profiles with firmographics, sector tags, and status Columns and Data Types is specific to Amazon Aurora and Company to Aviato — each maps to any object or custom field on the other side.
Primary and Foreign Keys Constraints used to identify records and preserve relational integrity in syncs. Person Founder and employee profiles linked to current and past companies Primary and Foreign Keys is specific to Amazon Aurora and Person to Aviato — each maps to any object or custom field on the other side.
Read Replicas Reader endpoints that syncs can target to keep load off the writer. Funding Round Round-level records with stage, amount, date, and participating investors Read Replicas is specific to Amazon Aurora and Funding Round to Aviato — each maps to any object or custom field on the other side.

How changes propagate between Amazon Aurora and Aviato

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 Aurora Aviato Sub-second propagation

DetectionChanges in Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.

DeliveryAviato does not accept inbound record writes, so this direction carries requests rather than records: Aviato's output flows back as field updates on the originating Amazon Aurora records.

Aviato Amazon Aurora Interval-based propagation

DetectionStacksync polls Aviato for changes on an incremental schedule, reading only records changed since the previous pass. Polling-based: re-query tracked records on a schedule and diff against the last synced state.

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

Rate-limit considerations

  • Amazon Aurora: No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits.
  • Aviato: Request volume is credit- and rate-limited per plan; schedule refreshes in batches rather than per-record calls.
What ships with Amazon Aurora ⇄ Aviato

Connect Amazon Aurora and Aviato for flexible, real-time data sync.

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Aurora or Aviato 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 Aurora or Aviato record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Aurora and Aviato.

How the Amazon Aurora and Aviato connectors work

Amazon Aurora

Integration surface
MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits

Aviato

Integration surface
REST API returning JSON, with search/filter endpoints for querying company and people records
Authentication
API key passed on each request
Change detection
Polling-based: re-query tracked records on a schedule and diff against the last synced state; no native change feed is assumed
Capabilities
read
Rate limits
Request volume is credit- and rate-limited per plan; schedule refreshes in batches rather than per-record calls
How it works

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

    Choose tables

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

Amazon Aurora and Aviato 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
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 214 integrations available for Amazon Aurora and Aviato.

Popular · 4 of 214
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