Real-time
Two-way sync
Changes in Dremio or Tinybird instantly reflect in both systems. No stale data, no manual imports.
Data warehouse
Dremio to Tinybird integration — real-time, two-way sync
Keep Dremio and Tinybird 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Dremio and Tinybird
Keep tables consistent across Dremio and Tinybird, for a migration, a multi-warehouse stack, or a dataset two platforms both need.
Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.
Stacksync syncs tables between Dremio and Tinybird continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.
Common use cases
- 01 Consolidate data from multiple lake sources through one Dremio semantic layer into a single warehouse target.
- 02 Sync curated Dremio views into an operational Postgres so applications get low-latency access to lakehouse data.
- 03 Stream CRM activity such as deals and tickets into Tinybird Data Sources to power customer-facing dashboards.
- 04 Sync order events from an ERP into Tinybird to serve low-latency operational analytics endpoints.
Common sync patterns
Consolidation after M&A
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
Migration without a big bang
When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Serve tools that only connect to one platform
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
What you can sync between Dremio and Tinybird
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.
| Dremio objects | Tinybird objects | How this pairing syncs | |
|---|---|---|---|
| Jobs Query execution records useful for monitoring sync workloads. | API Endpoints Published Pipe outputs exposed as parameterized HTTP queries; the main read surface. | Jobs is specific to Dremio and API Endpoints to Tinybird — each maps to any object or custom field on the other side. | |
| Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. | Materialized Views Pipes materialized into new Data Sources for pre-aggregation at ingest time. | Sources is specific to Dremio and Materialized Views to Tinybird — each maps to any object or custom field on the other side. | |
| Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. | Workspaces Project boundary that scopes Data Sources, Pipes, and tokens for a sync. | Physical datasets is specific to Dremio and Workspaces to Tinybird — each maps to any object or custom field on the other side. | |
| Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. | Tokens Scoped credentials that control read and append rights per resource. | Virtual datasets (views) is specific to Dremio and Tokens to Tinybird — each maps to any object or custom field on the other side. | |
| Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. | Data Sources ClickHouse-backed tables that receive ingested rows; the write target for syncs into Tinybird. | Apache Iceberg tables is specific to Dremio and Data Sources to Tinybird — each maps to any object or custom field on the other side. | |
| Spaces and folders Namespaces that organize virtual datasets and govern access. | Pipes Chained SQL nodes that transform Data Sources into query-ready results. | Spaces and folders is specific to Dremio and Pipes to Tinybird — each maps to any object or custom field on the other side. |
How changes propagate between Dremio and Tinybird
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.
Dremio Tinybird Interval-based propagation
DetectionStacksync polls Dremio for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL.
DeliveryEach detected change is applied to Tinybird as a row-level write, with types converted between the two schemas.
Tinybird Dremio Interval-based propagation
DetectionStacksync polls Tinybird for changes on an incremental schedule, reading only records changed since the previous pass. Append-oriented ingestion.
DeliveryEach detected change is applied to Dremio as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Dremio: Bounded by engine capacity and workload management rather than API rate limits.
- Tinybird: Subject to the platform's ingestion and query rate limits; batch appends where possible.
What ships with Dremio ⇄ Tinybird
Connect Dremio and Tinybird for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–Tinybird connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Dremio or Tinybird 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 Dremio or Tinybird record.
Observability
Monitoring
Track your Dremio ⇄ Tinybird sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Dremio and Tinybird.
How the Dremio and Tinybird connectors work
Dremio
- Integration surface
- Arrow Flight SQL, JDBC/ODBC, and a REST API
- Authentication
- Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud
- Change detection
- Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Bounded by engine capacity and workload management rather than API rate limits
Tinybird
- Integration surface
- REST API (Events API for ingestion, published query endpoints) with a ClickHouse SQL dialect
- Authentication
- Scoped auth tokens
- Change detection
- Append-oriented ingestion; reads are pulled by querying published endpoints, no outbound CDC
- Capabilities
- read · write
- Rate limits
- Subject to the platform's ingestion and query rate limits; batch appends where possible.
How it works
How to connect Dremio to Tinybird — 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 Dremio and Tinybird with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Dremio
connected
Tinybird
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Dremio and Tinybird 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 · Dremio ⇄ TinybirdCustomers 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.
Dremio TinybirdCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Dremio and Tinybird integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Dremio and Tinybird: authenticate both systems, choose the objects to sync (such as Dremio's Jobs and Sources), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Dremio and Tinybird connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Dremio–Tinybird integration in-house.
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Yes — Stacksync ships production-grade connectors for both Dremio and Tinybird. 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 Dremio: Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed. On Tinybird: Append-oriented ingestion; reads are pulled by querying published endpoints, no outbound CDC. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the Dremio side: Reflections, Jobs, Sources, Physical datasets, plus custom fields where Dremio exposes them. On the Tinybird side: Workspaces, Tokens, Data Sources, Pipes. Stacksync auto-detects both schemas and converts types between the two systems.
-
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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
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