Real-time
Two-way sync
Changes in Dremio or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Dremio to TimescaleDB integration — real-time, two-way sync
Keep Dremio and TimescaleDB 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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Migrated from Celigo
Why teams connect Dremio and TimescaleDB
Connect TimescaleDB and Dremio 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 TimescaleDB's rows in Dremio, 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 TimescaleDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in TimescaleDB sync into Dremio in real time, and result tables in Dremio sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.
Common use cases
- Consolidate data from multiple lake sources through one Dremio semantic layer into a single warehouse target.
- Sync curated Dremio views into an operational Postgres so applications get low-latency access to lakehouse data.
- Consolidate metrics from several services into one hypertable to serve a single reporting layer.
- Sync product or IoT telemetry stored in TimescaleDB into a CRM so account teams see usage metrics next to the customer record.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Offload heavy reads
Point analytical queries at the synced copy in Dremio and keep TimescaleDB focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from TimescaleDB land in Dremio as they change, replacing hand-built CDC and batch extract jobs.
What you can sync between Dremio and TimescaleDB
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 | TimescaleDB objects | |
|---|---|---|
| Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. | Views Standard SQL views used to shape or filter data for consumers. | |
| Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | |
| Spaces and folders Namespaces that organize virtual datasets and govern access. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | |
| Reflections Materialized accelerations that make repeated extraction queries cheaper. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | |
| Jobs Query execution records useful for monitoring sync workloads. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. |
What ships with Dremio ⇄ TimescaleDB
Connect Dremio and TimescaleDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–TimescaleDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Dremio or TimescaleDB 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 TimescaleDB record.
Observability
Monitoring
Track your Dremio ⇄ TimescaleDB 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 TimescaleDB.
How the Dremio and TimescaleDB 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
TimescaleDB
- Integration surface
- SQL wire protocol (PostgreSQL)
- Authentication
- Database credentials
- Change detection
- Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by database resources and connection limits.
How it works
How to connect Dremio to TimescaleDB — 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 TimescaleDB 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
TimescaleDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Dremio and TimescaleDB 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 ⇄ TimescaleDBCustomers 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 TimescaleDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Dremio and TimescaleDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Dremio and TimescaleDB: authenticate both systems, choose the objects to sync (such as Dremio's Virtual datasets (views) and Apache Iceberg tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Dremio side: Virtual datasets (views), Apache Iceberg tables, Spaces and folders, Reflections, plus custom fields where Dremio exposes them. On the TimescaleDB side: Chunks, Continuous Aggregates, Regular PostgreSQL Tables, Views. Stacksync auto-detects both schemas and converts types between the two systems.
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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.
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Common patterns for Dremio and TimescaleDB: Fresh analytics without loading windows; Offload heavy reads; Operational data in the warehouse, minus the pipeline. Because changes stream continuously, analysts query current data instead of waiting for last night's load.
-
Dremio: Arrow Flight SQL, JDBC/ODBC, and a REST API. Authentication: Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud. TimescaleDB: SQL wire protocol (PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
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Dremio: Virtual datasets let teams expose curated, governed views, so a sync can target business-ready SQL views instead of raw files. TimescaleDB: Hypertables automatically partition rows into time-based chunks while inserts and queries target the parent table. Stacksync's field mapping accounts for these differences between Dremio and TimescaleDB 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 Dremio and TimescaleDB.
Popular · 8 of 386
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Dremio ⇄ OpenSearch -
Dremio ⇄ Oracle DB -
Dremio ⇄ RavenDB -
Dremio ⇄ Redis Enterprise -
TimescaleDB ⇄ Google Cloud Platform -
TimescaleDB ⇄ Greenplum -
TimescaleDB ⇄ IBM Netezza -
TimescaleDB ⇄ Materialize
No integrations match .
