Real-time
Real-time sync
Changes in Apache Druid or Aviato instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Business productivity
Apache Druid to Aviato integration — real-time data sync
Keep Apache Druid 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.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Apache Druid and Aviato
Get the data locked inside Aviato into Apache Druid as live tables, and send results back where Aviato can use them, without writing a pipeline.
Aviato is a read-only source: Stacksync reads its data in real time and delivers it into Apache Druid, so Apache Druid always reflects the current state of Aviato — without exports, scripts, or schedulers.
Whatever Aviato is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
Common use cases
- 01 Keep a warehouse table of tracked private companies refreshed on a schedule for downstream scoring and reporting
- 02 Pull founder and team data into a sourcing database to flag new startups that match an investment thesis
- 03 Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.
- 04 Expose product telemetry stored in Druid to business tools without granting direct cluster access.
Common sync patterns
Cross-tool reporting
Combine Aviato's data with data from every other synced system to answer questions no single tool can.
Where Aviato accepts updates: operational write-back
Segments, scores, or reference values computed in Apache Druid sync back onto records in Aviato, putting analysis where the work happens.
History that outlives the tool
A continuously synced copy in Apache Druid preserves a queryable record even as data ages out of Aviato or gets changed inside it.
What you can sync between Apache Druid 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.
| Apache Druid objects | Aviato objects | How this pairing syncs | |
|---|---|---|---|
| Tasks Batch ingestion and compaction jobs monitored during data loads. | Investor Funds and angels connected to the rounds and companies they back | Tasks is specific to Apache Druid and Investor to Aviato — each maps to any object or custom field on the other side. | |
| Datasources The table-like unit of storage and querying, the main target of reads and ingestion. | Headcount Snapshot Point-in-time employee counts used to track company growth over time | Datasources is specific to Apache Druid and Headcount Snapshot to Aviato — each maps to any object or custom field on the other side. | |
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | Employment Record Person-to-company links with role and tenure that model team movement | Segments is specific to Apache Druid and Employment Record to Aviato — each maps to any object or custom field on the other side. | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | Acquisition / Exit Event M&A and exit records tied to the acquired company profile | Dimensions is specific to Apache Druid and Acquisition / Exit Event to Aviato — each maps to any object or custom field on the other side. | |
| Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | Company Private-company profiles with firmographics, sector tags, and status | Metrics is specific to Apache Druid and Company to Aviato — each maps to any object or custom field on the other side. | |
| Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. | Person Founder and employee profiles linked to current and past companies | Ingestion Supervisors is specific to Apache Druid and Person to Aviato — each maps to any object or custom field on the other side. |
How changes propagate between Apache Druid 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.
Apache Druid Aviato Interval-based propagation
DetectionStacksync polls Apache Druid for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Druid through streaming or batch ingestion rather than row updates.
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 Apache Druid records.
Aviato Apache Druid 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 Apache Druid as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Apache Druid: No fixed API quotas; query concurrency is bounded by broker and historical node capacity.
- Aviato: Request volume is credit- and rate-limited per plan; schedule refreshes in batches rather than per-record calls.
What ships with Apache Druid ⇄ Aviato
Connect Apache Druid and Aviato for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Aviato connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Druid 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 Apache Druid or Aviato record.
Observability
Monitoring
Track your Apache Druid ⇄ Aviato sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Apache Druid and Aviato.
How the Apache Druid and Aviato connectors work
Apache Druid
- Integration surface
- REST API (SQL over HTTP and native JSON queries); JDBC via Avatica
- Authentication
- Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy
- Change detection
- Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates
- Capabilities
- read · write
- Rate limits
- No fixed API quotas; query concurrency is bounded by broker and historical node capacity
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 Apache Druid 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.
- 01
Connect your apps
Authenticate Apache Druid 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.
Apache Druid
connected
Aviato
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Druid 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.
objects · Apache Druid ⇄ AviatoCustomers 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.
Apache Druid AviatoCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Druid and Aviato integration FAQ
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Yes. Stacksync provides a managed, real-time integration between Apache Druid and Aviato — 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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Yes — Stacksync ships production-grade connectors for both Apache Druid and Aviato. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Apache Druid: Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates. On Aviato: Polling-based: re-query tracked records on a schedule and diff against the last synced state; no native change feed is assumed. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Aviato side: Headcount Snapshot, Employment Record, Acquisition / Exit Event, Company, plus custom fields where Aviato exposes them. On the Apache Druid side: Tasks, Datasources, Segments, Dimensions. 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 Apache Druid. Field mapping and monitoring work the same as for two-way pairs.
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Common patterns for Apache Druid and Aviato: Cross-tool reporting; Where Aviato accepts updates: operational write-back; History that outlives the tool. Combine Aviato's data with data from every other synced system to answer questions no single tool can.
SECURITY
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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.
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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
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