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

Keep Jms 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.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Jms and VoltDB

Keep VoltDB and Jms in step: the rows in your database and the BytesMessage, Durable Subscription, Message headers and properties, Dead Letter Queue your engineering tools track stay consistent in real time, in both directions.

VoltDB is where your application's durable data lives; Jms is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.

Stacksync syncs Export Targets and Topics, Partitioned Tables, Replicated Tables, Stored Procedures in VoltDB with BytesMessage, Durable Subscription, Message headers and properties, Dead Letter Queue in Jms field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.

Common use cases

  • 01 Push aggregates from VoltDB materialized views into dashboards or operational tools.
  • 02 Sync customer or account reference data from a CRM into VoltDB replicated tables for in-transaction lookups such as fraud or policy checks.
  • 03 Consume order or event messages from a JMS Queue and upsert them as rows into Postgres or a warehouse so downstream apps read them in plain SQL.
  • 04 Publish records changed in a CRM or database as TextMessages onto a JMS Topic so subscribing Java services react in real time.

Common sync patterns

Land tool activity as queryable rows

Records and events from Jms arrive in VoltDB as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.

One integration pattern instead of per-tool API code

Read and write the synced tables in VoltDB and Stacksync keeps Jms current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.

React to changes on either side in near real time

Updates in Jms arrive as row changes in VoltDB, and writes to VoltDB propagate to Jms within seconds, so triggers, jobs, and alerts fire without polling.

What you can sync between Jms 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.

Jms objects VoltDB objects How this pairing syncs
Dead Letter Queue Provider-managed destination (e.g. ActiveMQ.DLQ, IBM MQ dead-letter queue) where messages exceeding redelivery limits land; read to reconcile failed deliveries. Export Targets and Topics Connectors that push committed data to external systems such as Kafka or JDBC sinks. Dead Letter Queue is specific to Jms and Export Targets and Topics to VoltDB — each maps to any object or custom field on the other side.
Queue Point-to-point destination where each message is delivered to exactly one consumer. Stacksync consumes messages to load into a database, or publishes messages for a downstream Java service to process. Partitioned Tables Tables sharded across partitions by a partitioning column; the primary transactional store and sync target. Queue is specific to Jms and Partitioned Tables to VoltDB — each maps to any object or custom field on the other side.
Topic Publish/subscribe destination that fans each message out to every active subscriber. Stacksync subscribes to event streams or publishes records so multiple services react. Replicated Tables Small reference tables copied to every partition, a common landing spot for synced lookup data. Topic is specific to Jms and Replicated Tables to VoltDB — each maps to any object or custom field on the other side.
TextMessage Most common body type, carrying a String that is usually JSON or XML. Deserialized into rows/records on read and serialized from source records on write. Stored Procedures Precompiled transactional units that serve as the primary write interface. TextMessage is specific to Jms and Stored Procedures to VoltDB — each maps to any object or custom field on the other side.
MapMessage Body of typed name/value pairs that maps directly onto record fields, so no custom body parsing is needed on read or write. Materialized Views Synchronously maintained aggregates over tables, useful as pre-computed read sources. MapMessage is specific to Jms and Materialized Views to VoltDB — each maps to any object or custom field on the other side.
BytesMessage Raw binary body for files, protobuf, or opaque payloads; passed through as a byte stream when structured field mapping is not required. Streams Insert-only constructs that feed the export subsystem with committed rows. BytesMessage is specific to Jms and Streams to VoltDB — each maps to any object or custom field on the other side.

How changes propagate between Jms 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.

Jms VoltDB Sub-second propagation

DetectionJms notifies Stacksync of record changes through webhook events. Asynchronous push — the broker delivers messages to registered consumers (MessageListener.onMessage) in real time, with no polling.

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

VoltDB Jms 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 written to Jms through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Jms: JMS defines no protocol-level rate limits; throughput ceilings, consumer prefetch, and producer flow control are configured on the broker (ActiveMQ, IBM MQ, Solace, TIBCO EMS, etc.).
  • VoltDB: No API rate limits; throughput is bounded by partition count and cluster sizing.
What ships with Jms ⇄ VoltDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jms 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 Jms or VoltDB record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Jms and VoltDB connectors work

Jms

Integration surface
JMS / Jakarta Messaging API (classic API and simplified JMSContext) over provider transports such as OpenWire, AMQP, IBM MQ, or STOMP
Authentication
Username/password credentials passed to ConnectionFactory.createConnection(); ConnectionFactory and Destinations resolved via JNDI. Transport security (TLS) and stronger auth (SASL, JAAS, client certificates) are broker-implementation-specific.
Change detection
Asynchronous push — the broker delivers messages to registered consumers (MessageListener.onMessage) in real time, with no polling. Message selectors (an SQL-92 subset over headers/properties) filter delivery. There is no modified-date polling or CDC replay, and queue consumption is destructive.
Capabilities
read · write · webhooks
Rate limits
JMS defines no protocol-level rate limits; throughput ceilings, consumer prefetch, and producer flow control are configured on the broker (ActiveMQ, IBM MQ, Solace, TIBCO EMS, etc.).

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

    Choose tables

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

Jms 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
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 324 integrations available for Jms and VoltDB.

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