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Data warehouse ⇄ Database

Databricks to VoltDB integration — real-time, two-way sync

Keep Databricks and VoltDB 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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Why teams connect Databricks and VoltDB

Connect VoltDB and Databricks 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 VoltDB's rows in Databricks, 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 VoltDB where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in VoltDB sync into Databricks in real time, and result tables in Databricks sync back into VoltDB, with schema and type mapping between the two systems handled for you.

Common use cases

  • Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • Stream committed VoltDB results out through export targets into a warehouse for historical analysis.
  • Keep product, plan, or entitlement state consistent between VoltDB and back-office systems.

Offload heavy reads

Point analytical queries at the synced copy in Databricks and keep VoltDB focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from VoltDB land in Databricks as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Databricks sync into VoltDB, where whatever reads from that database gets them without querying the warehouse.

What you can sync between Databricks and VoltDB

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.

Databricks objects VoltDB objects
Volumes Unity Catalog file storage used for staging bulk loads. Partitioned Tables Tables sharded across partitions by a partitioning column; the primary transactional store and sync target.
SQL Warehouses The compute endpoint a sync connects to for query execution. Replicated Tables Small reference tables copied to every partition, a common landing spot for synced lookup data.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Stored Procedures Precompiled transactional units that serve as the primary write interface.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Materialized Views Synchronously maintained aggregates over tables, useful as pre-computed read sources.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Streams Insert-only constructs that feed the export subsystem with committed rows.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Export Targets and Topics Connectors that push committed data to external systems such as Kafka or JDBC sinks.
What ships with Databricks ⇄ VoltDB

Connect Databricks and VoltDB for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Databricks or VoltDB instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or VoltDB 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 Databricks or VoltDB record.

Observability

Monitoring

Track your Databricks ⇄ VoltDB sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Databricks and VoltDB.

How the Databricks and VoltDB connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

VoltDB

Integration surface
SQL over JDBC plus native client libraries and an HTTP/JSON interface
Authentication
Database credentials
Change detection
Export streams and topics push committed changes to configured targets; otherwise polling
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by partition count and cluster sizing.
How it works

How to connect Databricks to VoltDB — 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 Databricks and VoltDB 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
    Databricks connected
    VoltDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks and VoltDB 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 · Databricks ⇄ VoltDB
    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
    Databricks VoltDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and VoltDB 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 Databricks and VoltDB.

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