Real-time
Two-way sync
Changes in Cloudera Data Platform or Dremio instantly reflect in both systems. No stale data, no manual imports.
Data warehouse
Cloudera Data Platform to Dremio integration — real-time, two-way sync
Keep Cloudera Data Platform and Dremio 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 Cloudera Data Platform and Dremio
Keep tables consistent across Cloudera Data Platform and Dremio, 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 Cloudera Data Platform and Dremio 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
- Consolidate tables from on-prem and cloud CDP environments into a single cloud warehouse target.
- Sync curated CDP tables into an operational Postgres so applications query a low-latency copy instead of hitting the cluster.
- Publish operational database tables into Iceberg via Dremio so the lakehouse reflects current application state.
- Consolidate data from multiple lake sources through one Dremio semantic layer into a single warehouse target.
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 Cloudera Data Platform and Dremio
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.
| Cloudera Data Platform objects | Dremio objects | |
|---|---|---|
| Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. | Jobs Query execution records useful for monitoring sync workloads. | |
| Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. | |
| Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. | |
| Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. | |
| Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. | |
| Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. | Spaces and folders Namespaces that organize virtual datasets and govern access. |
What ships with Cloudera Data Platform ⇄ Dremio
Connect Cloudera Data Platform and Dremio for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cloudera Data Platform–Dremio connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Cloudera Data Platform or Dremio 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 Cloudera Data Platform or Dremio record.
Observability
Monitoring
Track your Cloudera Data Platform ⇄ Dremio sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Cloudera Data Platform and Dremio.
How the Cloudera Data Platform and Dremio connectors work
Cloudera Data Platform
- Integration surface
- JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs
- Authentication
- Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway
- Change detection
- Polling via SQL on timestamp or partition columns; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Constrained by cluster capacity and admission control rather than API rate limits
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
How it works
How to connect Cloudera Data Platform to Dremio — 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 Cloudera Data Platform and Dremio with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Cloudera Data Platform
connected
Dremio
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Cloudera Data Platform and Dremio 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 · Cloudera Data Platform ⇄ DremioCustomers 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.
Cloudera Data Platform DremioCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Cloudera Data Platform and Dremio integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Cloudera Data Platform and Dremio: authenticate both systems, choose the objects to sync (such as Cloudera Data Platform's Object store / HDFS files and Databases), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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 Cloudera Data Platform and Dremio: Consolidation after M&A; Migration without a big bang; Serve tools that only connect to one platform. Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
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Cloudera Data Platform: JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs. Authentication: Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway. Dremio: Arrow Flight SQL, JDBC/ODBC, and a REST API. Authentication: Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud. Stacksync manages authentication, retries, and rate limits on both sides.
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Cloudera Data Platform: Access is commonly brokered by Apache Knox and secured with Kerberos or LDAP, which integration tooling must support. Dremio: DML (INSERT, UPDATE, DELETE) is supported on Apache Iceberg tables, making Dremio a writable target, not just a query layer. Stacksync's field mapping accounts for these differences between Cloudera Data Platform and Dremio without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Cloudera Data Platform and Dremio records are not retained after a sync operation.
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 Cloudera Data Platform and Dremio.
Popular · 8 of 386
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Cloudera Data Platform ⇄ Starburst Enterprise -
Cloudera Data Platform ⇄ StarRocks -
Cloudera Data Platform ⇄ Teradata Vantage -
Cloudera Data Platform ⇄ Tinybird -
Dremio ⇄ Vertica -
Dremio ⇄ Yellowbrick -
Dremio ⇄ Snowflake -
Dremio ⇄ BigQuery
No integrations match .
