Real-time
Real-time sync
Changes in Aviato or AWS Aurora MySQL instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Database
Aviato to AWS Aurora MySQL integration — real-time data sync
Keep Aviato and AWS Aurora MySQL 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 Aviato and AWS Aurora MySQL
Mirror Aviato's data into AWS Aurora MySQL 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 AWS Aurora MySQL, so AWS Aurora MySQL 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 AWS Aurora MySQL.
Stacksync mirrors Investor, Headcount Snapshot, Employment Record, Acquisition / Exit Event from Aviato into Stored procedures and triggers, Databases (schemas), Tables, Rows in AWS Aurora MySQL 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
- Feed lead-scoring models with growth signals (funding recency, headcount trajectory) pulled from Aviato
- Backfill missing firmographic fields on inbound leads by matching them to Aviato company profiles
- Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
- Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.
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.
Read Aviato with a query
Records from Aviato are ordinary rows in AWS Aurora MySQL; join them, index them, and use them in application logic without touching the vendor API.
Automate Aviato from your codebase
Write to the synced tables in AWS Aurora MySQL and Stacksync propagates the change into Aviato, replacing custom integration code.
What you can sync between Aviato and AWS Aurora MySQL
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.
| Aviato objects | AWS Aurora MySQL objects | |
|---|---|---|
| Person Founder and employee profiles linked to current and past companies | Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | |
| Funding Round Round-level records with stage, amount, date, and participating investors | Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | |
| Investor Funds and angels connected to the rounds and companies they back | Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | |
| Headcount Snapshot Point-in-time employee counts used to track company growth over time | Columns MySQL data types are mapped to the paired system's field types during schema setup. | |
| Employment Record Person-to-company links with role and tenure that model team movement | Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | |
| Acquisition / Exit Event M&A and exit records tied to the acquired company profile | Views Can serve as read-only sync sources for derived or filtered datasets. |
What ships with Aviato ⇄ AWS Aurora MySQL
Connect Aviato and AWS Aurora MySQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Aviato–AWS Aurora MySQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Aviato or AWS Aurora MySQL 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 Aviato or AWS Aurora MySQL record.
Observability
Monitoring
Track your Aviato ⇄ AWS Aurora MySQL sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Aviato and AWS Aurora MySQL.
How the Aviato and AWS Aurora MySQL connectors work
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
AWS Aurora MySQL
- Integration surface
- SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
- Authentication
- Database credentials, optionally AWS IAM database authentication, over TLS
- Change detection
- Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
- Capabilities
- read · write · CDC
How it works
How to connect Aviato to AWS Aurora MySQL — 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.
- 01
Connect your apps
Authenticate Aviato and AWS Aurora MySQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Aviato
connected
AWS Aurora MySQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Aviato and AWS Aurora MySQL 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.
objects · Aviato ⇄ AWS Aurora MySQLCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Aviato AWS Aurora MySQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Aviato and AWS Aurora MySQL integration FAQ
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Yes. Stacksync provides a managed, real-time integration between Aviato and AWS Aurora MySQL — Aviato is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
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On the Aviato side: Investor, Headcount Snapshot, Employment Record, Acquisition / Exit Event, plus custom fields where Aviato exposes them. On the AWS Aurora MySQL side: Stored procedures and triggers, Databases (schemas), Tables, Rows. Stacksync auto-detects both schemas and converts types between the two systems.
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Aviato is a read-only source, so this integration runs one-way: Stacksync reads from Aviato in real time and delivers into AWS Aurora MySQL. Field mapping and monitoring work the same as for two-way pairs.
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Common patterns for Aviato and AWS Aurora MySQL: One integration pattern for the whole stack; Read Aviato with a query; Automate Aviato from your codebase. Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.
-
Aviato: REST API returning JSON, with search/filter endpoints for querying company and people records. Authentication: API key passed on each request. AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
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Aviato: Aviato's data model centers on private-market entities — companies, the people behind them, and the funding events connecting them — rather than user-created business records. AWS Aurora MySQL: Aurora separates compute from a distributed storage layer that replicates data six ways across three Availability Zones, independent of the instances that CDC readers and sync writers connect to. Stacksync's field mapping accounts for these differences between Aviato and AWS Aurora MySQL without custom code.
SECURITY
Security teams love 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 386 integrations available for Aviato and AWS Aurora MySQL.
Popular · 8 of 386
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Aviato ⇄ YugabyteDB -
Aviato ⇄ PostgreSQL -
Aviato ⇄ Amazon RDS -
Aviato ⇄ Supabase -
AWS Aurora MySQL ⇄ Lusha -
AWS Aurora MySQL ⇄ Microsoft 365 -
AWS Aurora MySQL ⇄ Microsoft Dynamics 365 -
AWS Aurora MySQL ⇄ Microsoft Teams
No integrations match .
