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Data warehouse

Dremio to Vertica integration — real-time, two-way sync

Keep Dremio and Vertica 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
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Dremio and Vertica

Keep tables consistent across Dremio and Vertica, 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 Vertica 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

  • Sync curated Dremio views into an operational Postgres so applications get low-latency access to lakehouse data.
  • Reverse-ETL aggregates computed over lake data out to CRMs and finance tools for business users.
  • Sync CRM accounts and opportunities into Vertica to join with large-scale behavioral or telemetry data.
  • Land ERP transactions in Vertica for finance analytics without maintaining hand-built ETL jobs.

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.

Shared datasets across teams

Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.

What you can sync between Dremio and Vertica

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 Vertica objects
Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. External Tables Data queried in place on files or object storage without loading.
Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. Schemas Namespaces used to organize synced datasets by domain or source.
Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. Tables Columnar tables; the primary read and write targets for syncs.
Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. Projections Sorted, encoded physical copies of table data that the optimizer selects at query time; they affect load and query behavior rather than being addressed directly.
Spaces and folders Namespaces that organize virtual datasets and govern access. Views Logical views used to shape reads for downstream consumers.
Reflections Materialized accelerations that make repeated extraction queries cheaper. Flex Tables Schema-flexible tables for semi-structured JSON data landed before modeling.
What ships with Dremio ⇄ Vertica

Connect Dremio and Vertica for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–Vertica connection.

Real-time

Two-way sync

Changes in Dremio or Vertica instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Dremio or Vertica 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 Vertica record.

Observability

Monitoring

Track your Dremio ⇄ Vertica 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 Vertica.

How the Dremio and Vertica 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

Vertica

Integration surface
SQL over JDBC, ODBC, and ADO.NET drivers
Authentication
Database credentials, with LDAP, Kerberos, and OAuth options in enterprise deployments
Change detection
No exposed transaction-log CDC; polling on timestamp or epoch columns
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by cluster resources, and bulk COPY is preferred over row-by-row writes.
How it works

How to connect Dremio to Vertica — 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.

  1. 01

    Connect your apps

    Authenticate Dremio and Vertica with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Dremio connected
    Vertica connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Dremio and Vertica 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Dremio ⇄ Vertica
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Dremio Vertica
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Dremio and Vertica integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Dremio and Vertica.

Popular · 8 of 386
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