Skip to content
Data warehouse

Apache Druid to Vertica integration — real-time, two-way sync

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

Keep tables consistent across Apache Druid 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 Apache Druid 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 Druid query results into a warehouse to combine real-time aggregates with historical models.
  • Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.
  • Land ERP transactions in Vertica for finance analytics without maintaining hand-built ETL jobs.
  • Push segments or aggregates computed in Vertica back into operational tools such as a CRM.

Shared datasets across teams

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

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.

What you can sync between Apache Druid 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.

Apache Druid objects Vertica objects
Tasks Batch ingestion and compaction jobs monitored during data loads. External Tables Data queried in place on files or object storage without loading.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Schemas Namespaces used to organize synced datasets by domain or source.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Tables Columnar tables; the primary read and write targets for syncs.
Dimensions String and categorical columns used for filtering and grouping in synced queries. 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.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Views Logical views used to shape reads for downstream consumers.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Flex Tables Schema-flexible tables for semi-structured JSON data landed before modeling.
What ships with Apache Druid ⇄ Vertica

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid 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 Apache Druid or Vertica record.

Observability

Monitoring

Track your Apache Druid ⇄ Vertica 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 Vertica.

How the Apache Druid and Vertica 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

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 Apache Druid 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 Apache Druid 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
    Apache Druid connected
    Vertica connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Druid 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 · Apache Druid ⇄ 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
    Apache Druid Vertica
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Apache Druid 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 Apache Druid and Vertica.

Popular · 8 of 386
All Apache Druid integrations All Vertica integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own