Real-time
Two-way sync
Changes in Jdbc or Recurly instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Accounting and finance
Jdbc to Recurly integration — real-time, two-way sync
Keep Jdbc and Recurly 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
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Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Jdbc and Recurly
Work with Recurly's financial data straight from Jdbc: read it with ordinary queries, write to it from your own code, and let Stacksync keep both sides consistent.
Engineers need finance data more often than finance systems make it easy to get: for internal tools, reporting services, or logic that reacts to invoices and payments. Working through the vendor API means rate limits, pagination, and glue code that has to be maintained forever.
Stacksync mirrors Invoices, Transactions, Line Items, Coupons and Redemptions from Recurly into Stored procedures & functions, Sequences, Tables, Views in Jdbc and keeps the two in sync bi-directionally and in real time. Your services read finance records with normal queries against Jdbc, and rows your code writes or updates flow back into Recurly with validation, so the finance system stays the system of record.
Common use cases
- 01 Trigger revenue-recognition or ERP entries when new_subscription and canceled_subscription webhooks fire.
- 02 Post usage records to Measured Units on metered Subscriptions from a metering database before each bill run.
- 03 Incrementally sync a high-volume table by polling an updated_at or auto-increment column, keeping a downstream store fresh without full reloads.
- 04 Consolidate several databases from different vendors into one relational store by syncing each through its own JDBC driver.
Common sync patterns
Write back safely
Updates written to the synced tables in Jdbc propagate into Recurly, so automations can create or correct finance records without custom integration code.
React to financial events
Changes in Recurly appear in Jdbc as row changes, so you can trigger downstream logic with the database tooling you already use.
Query finance data like any other data
Customers, invoices, and payments from Recurly live in Jdbc as regular tables or collections your team can join, index, and query.
What you can sync between Jdbc and Recurly
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.
| Jdbc objects | Recurly objects | How this pairing syncs | |
|---|---|---|---|
| Views Stored SELECT queries exposed like tables; read-only projections synced outbound when raw base tables should not be exposed downstream. | Line Items One-time charges and credits on an account outside a subscription; synced for accurate revenue and adjustment reporting. | Views is specific to Jdbc and Line Items to Recurly — each maps to any object or custom field on the other side. | |
| Columns Per-table fields with data types, nullability, and defaults; enumerated via DatabaseMetaData.getColumns to auto-generate and type-check field mappings. | Coupons and Redemptions Discount definitions and their application to accounts and subscriptions; read for discount and promotion analysis. | Columns is specific to Jdbc and Coupons and Redemptions to Recurly — each maps to any object or custom field on the other side. | |
| Primary keys & indexes Key and index definitions read via DatabaseMetaData; the primary key is required for reliable upserts, and indexes on the cursor column keep incremental polling fast. | Billing Info Tokenized payment method (card/ACH) on an account; written when onboarding customers and read for payment-health signals (never stores raw card numbers). | Primary keys & indexes is specific to Jdbc and Billing Info to Recurly — each maps to any object or custom field on the other side. | |
| Schemas & catalogs Namespaces that group tables and views; the connector targets a schema/catalog and lists its objects from the JDBC metadata to build the sync. | Measured Units and Usage Metered-billing units; usage records are posted to a subscription before each bill run for consumption-based pricing. | Schemas & catalogs is specific to Jdbc and Measured Units and Usage to Recurly — each maps to any object or custom field on the other side. | |
| Stored procedures & functions Server-side routines callable via JDBC CallableStatement; invoked for custom read or write logic when a table-level mapping is not enough. | Accounts Customer/billing entity records keyed by account_code; the anchor most subscriptions and invoices hang off. Synced two-way with CRM accounts or a customer database. | Stored procedures & functions is specific to Jdbc and Accounts to Recurly — each maps to any object or custom field on the other side. | |
| Sequences Server-generated identity values; relevant when writing rows into tables whose keys are assigned by the database rather than the source system. | Subscriptions Recurring subscription records tied to an Account and a Plan, with state, term, and next-bill date. Core object, synced two-way to drive provisioning and reporting. | Sequences is specific to Jdbc and Subscriptions to Recurly — each maps to any object or custom field on the other side. |
How changes propagate between Jdbc and Recurly
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.
Jdbc Recurly Interval-based propagation
DetectionStacksync polls Jdbc for changes on an incremental schedule, reading only records changed since the previous pass. No native change feed.
DeliveryEach detected change is written to Recurly through its API, with automatic retries and rate-limit backoff.
Recurly Jdbc Sub-second propagation
DetectionRecurly notifies Stacksync of record changes through webhook events. Webhooks (JSON or XML, one format per endpoint) for account, subscription, payment, and invoice events, plus incremental polling of list endpoints.
DeliveryEach detected change is applied to Jdbc as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Jdbc: No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.
- Recurly: Production sites default to 1,000 requests/min with only GET requests counting toward the limit; sandbox sites 400/min with all requests counting; the limit is a sliding 5-minute window, X-RateLimit headers report the quota, and breaches return HTTP 429.
What ships with Jdbc ⇄ Recurly
Connect Jdbc and Recurly for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jdbc–Recurly connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Jdbc or Recurly 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 Jdbc or Recurly record.
Observability
Monitoring
Track your Jdbc ⇄ Recurly sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Jdbc and Recurly.
How the Jdbc and Recurly connectors work
Jdbc
- Integration surface
- JDBC API (java.sql / javax.sql) executing SQL through a JDBC driver, typically a pure-Java Type 4 driver; reaches any relational database with a driver - PostgreSQL, MySQL, SQL Server, Oracle, IBM DB2, and others - via a JDBC URL such as jdbc:postgresql://host:5432/db.
- Authentication
- A database user's username and password supplied in the JDBC connection (DriverManager or a DataSource), typically over a TLS/SSL-encrypted connection. Some drivers add Kerberos, integrated Windows auth, or cloud IAM-token auth, but the available methods depend on the target database and its driver.
- Change detection
- No native change feed. Incremental sync polls a cursor column - an updated_at timestamp or an auto-incrementing key - to pull new and changed rows; detecting deletes needs soft-delete flags or database triggers writing to a shadow table. No webhooks.
- Capabilities
- read · write
- Rate limits
- No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.
Recurly
- Integration surface
- REST API (V3, date-versioned; legacy V2 XML API also exists)
- Authentication
- API key via HTTP Basic auth (key as username, blank password); keys are per-site, with separate sandbox and production keys
- Change detection
- Webhooks (JSON or XML, one format per endpoint) for account, subscription, payment, and invoice events, plus incremental polling of list endpoints sorted by updated_at with begin_time/end_time filters
- Capabilities
- read · write · webhooks
- Rate limits
- Production sites default to 1,000 requests/min with only GET requests counting toward the limit; sandbox sites 400/min with all requests counting; the limit is a sliding 5-minute window, X-RateLimit headers report the quota, and breaches return HTTP 429.
How it works
How to connect Jdbc to Recurly — 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.
- 01
Connect your apps
Authenticate Jdbc and Recurly with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Jdbc connected
Recurly
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Jdbc and Recurly 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.
objects · Jdbc ⇄ RecurlyCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Jdbc RecurlyCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Jdbc and Recurly integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Jdbc and Recurly: authenticate both systems, choose the objects to sync (such as Jdbc's Views and Columns), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Recurly: List endpoints support incremental pulls via sort=updated_at (or created_at) with begin_time/end_time filters, so polling fetches only records changed since the last run. Jdbc: There is no native change feed - incremental sync needs a cursor column (an updated_at timestamp or an auto-incrementing key), and detecting deletes requires soft-delete flags or triggers because a plain SELECT cannot see removed rows. Stacksync's field mapping accounts for these differences between Jdbc and Recurly without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Jdbc and Recurly records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Jdbc and Recurly connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Jdbc–Recurly integration in-house.
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Yes — Stacksync ships production-grade connectors for both Jdbc and Recurly. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Jdbc: No native change feed. Incremental sync polls a cursor column - an updated_at timestamp or an auto-incrementing key - to pull new and changed rows; detecting deletes needs soft-delete flags or database triggers writing to a shadow table. No webhooks. On Recurly: Webhooks (JSON or XML, one format per endpoint) for account, subscription, payment, and invoice events, plus incremental polling of list endpoints sorted by updated_at with begin_time/end_time filters. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 426 integrations available for Jdbc and Recurly.
Popular · 7 of 426
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Jdbc ⇄ Bill -
Jdbc ⇄ Braintree -
Jdbc ⇄ Navan -
Recurly ⇄ Redis Enterprise -
Recurly ⇄ SAP ASE (Sybase) -
Recurly ⇄ Scaleway Postgres -
Recurly ⇄ TiDB
No integrations match .
