Skip to content
Data warehouse ⇄ Database

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

Keep Dremio 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

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 Dremio and VoltDB

Connect VoltDB 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 VoltDB'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 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 Dremio in real time, and result tables in Dremio sync back into VoltDB, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Publish operational database tables into Iceberg via Dremio so the lakehouse reflects current application state.
  • 02 Consolidate data from multiple lake sources through one Dremio semantic layer into a single warehouse target.
  • 03 Push aggregates from VoltDB materialized views into dashboards or operational tools.
  • 04 Sync customer or account reference data from a CRM into VoltDB replicated tables for in-transaction lookups such as fraud or policy checks.

Common sync patterns

Serve warehouse results at database speed

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

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 VoltDB focused on its operational workload.

What you can sync between Dremio 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.

Dremio objects VoltDB objects How this pairing syncs
Spaces and folders Namespaces that organize virtual datasets and govern access. Replicated Tables Small reference tables copied to every partition, a common landing spot for synced lookup data. Spaces and folders is specific to Dremio and Replicated Tables to VoltDB — each maps to any object or custom field on the other side.
Reflections Materialized accelerations that make repeated extraction queries cheaper. Stored Procedures Precompiled transactional units that serve as the primary write interface. Reflections is specific to Dremio and Stored Procedures to VoltDB — each maps to any object or custom field on the other side.
Jobs Query execution records useful for monitoring sync workloads. Materialized Views Synchronously maintained aggregates over tables, useful as pre-computed read sources. Jobs is specific to Dremio and Materialized Views to VoltDB — each maps to any object or custom field on the other side.
Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. Streams Insert-only constructs that feed the export subsystem with committed rows. Sources is specific to Dremio and Streams to VoltDB — each maps to any object or custom field on the other side.
Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. Export Targets and Topics Connectors that push committed data to external systems such as Kafka or JDBC sinks. Physical datasets is specific to Dremio and Export Targets and Topics to VoltDB — each maps to any object or custom field on the other side.
Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. Partitioned Tables Tables sharded across partitions by a partitioning column; the primary transactional store and sync target. Virtual datasets (views) is specific to Dremio and Partitioned Tables to VoltDB — each maps to any object or custom field on the other side.

How changes propagate between Dremio and VoltDB

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Dremio VoltDB Interval-based propagation

DetectionStacksync polls Dremio for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL.

DeliveryEach detected change is applied to VoltDB as a row-level write, with types converted between the two schemas.

VoltDB Dremio Interval-based propagation

DetectionStacksync polls VoltDB for changes on an incremental schedule, reading only records changed since the previous pass. Export streams and topics push committed changes to configured targets.

DeliveryEach detected change is applied to Dremio as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Dremio: Bounded by engine capacity and workload management rather than API rate limits.
  • VoltDB: No API rate limits; throughput is bounded by partition count and cluster sizing.
What ships with Dremio ⇄ VoltDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Dremio 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 Dremio or VoltDB record.

Observability

Monitoring

Track your Dremio ⇄ VoltDB 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 VoltDB.

How the Dremio and VoltDB 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

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

    Choose tables

    Pick the Dremio 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 · Dremio ⇄ 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
    Dremio VoltDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Dremio and VoltDB integration FAQ

SECURITY

Security teams trust 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 392 integrations available for Dremio and VoltDB.

Popular · 8 of 392
All Dremio integrations All VoltDB 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