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Developer tools ⇄ Database

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

Keep Jms and SingleStore 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 SingleStore

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

SingleStore 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 Views, Reference Tables, Pipelines, Stored Procedures in SingleStore with Durable Subscription, Message headers and properties, Dead Letter Queue, 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 Consolidate data from transactional databases and SaaS apps into one store that handles both lookups and scans.
  • 02 Keep reference data consistent between SingleStore and application databases.
  • 03 Fan out inventory or pricing updates onto a Topic with durable subscriptions so multiple services stay aligned even after downtime.
  • 04 Route messages by JMSType or application property using a message selector, landing high-priority messages in one table and the rest in another.

Common sync patterns

Where Jms manages users or groups: keep identity aligned

Directory and identity records in Jms stay matched to the users or owners table in SingleStore, so provisioning and de-provisioning flow from one source.

Turn rows into the records your tools track

A new or changed row in SingleStore creates or updates the matching record in Jms, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.

Land tool activity as queryable rows

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

What you can sync between Jms and SingleStore

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 SingleStore objects How this pairing syncs
MapMessage Body of typed name/value pairs that maps directly onto record fields, so no custom body parsing is needed on read or write. Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans. MapMessage is specific to Jms and Tables (rowstore and columnstore) to SingleStore — 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. Views Read-only projections used as curated sync sources. BytesMessage is specific to Jms and Views to SingleStore — each maps to any object or custom field on the other side.
Durable Subscription Named topic subscription that retains messages while the consumer is offline, so a sync that disconnects does not miss events published in the meantime. Reference Tables Small tables replicated to every node, often used for dimension data in syncs. Durable Subscription is specific to Jms and Reference Tables to SingleStore — each maps to any object or custom field on the other side.
Message headers and properties JMSCorrelationID, JMSReplyTo, JMSTimestamp, JMSType plus JMSX/application-defined properties; used for correlation, routing, and selector-based filtering. Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs. Message headers and properties is specific to Jms and Pipelines to SingleStore — each maps to any object or custom field on the other side.
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. Stored Procedures Existing logic sometimes invoked on write paths. Dead Letter Queue is specific to Jms and Stored Procedures to SingleStore — 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. Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys. Queue is specific to Jms and Indexes and Shard Keys to SingleStore — each maps to any object or custom field on the other side.

How changes propagate between Jms and SingleStore

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 SingleStore 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 SingleStore as a row-level write, with types converted between the two schemas.

SingleStore Jms Interval-based propagation

DetectionStacksync polls SingleStore for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or watermark columns.

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.).
  • SingleStore: No API rate limits; throughput is bounded by workspace or cluster size.
What ships with Jms ⇄ SingleStore

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jms or SingleStore 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 SingleStore record.

Observability

Monitoring

Track your Jms ⇄ SingleStore 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 SingleStore.

How the Jms and SingleStore 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.).

SingleStore

Integration surface
SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
Authentication
Database credentials
Change detection
Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by workspace or cluster size
How it works

How to connect Jms to SingleStore — 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 SingleStore 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
    SingleStore connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Jms and SingleStore 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 328 integrations available for Jms and SingleStore.

Popular · 8 of 328
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