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Database ⇄ Developer tools

Jdbc to Newrelic integration — real-time, two-way sync

Keep Jdbc and Newrelic 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 Jdbc and Newrelic

Keep Jdbc and Newrelic in step: the rows in your database and the Change Tracking (Deployments), Dashboards, Alert Policies & Conditions, NRQL Query Results your engineering tools track stay consistent in real time, in both directions.

Jdbc is where your application's durable data lives; Newrelic 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 Columns, Primary keys & indexes, Schemas & catalogs, Stored procedures & functions in Jdbc with Change Tracking (Deployments), Dashboards, Alert Policies & Conditions, NRQL Query Results in Newrelic 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 several databases from different vendors into one relational store by syncing each through its own JDBC driver.
  • 02 Write records from a CRM, ERP, or another app back into database tables via SQL INSERT and UPDATE so the database stays current.
  • 03 Sync the Entity catalog into a CMDB or warehouse for asset inventory, and add or replace entity Tags to keep ownership and environment metadata current.
  • 04 Provision Synthetics Monitors from a service catalog and read their results via NRQL for availability and latency reporting in SQL.

Common sync patterns

Turn rows into the records your tools track

A new or changed row in Jdbc creates or updates the matching record in Newrelic, 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 Newrelic arrive in Jdbc 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 Jdbc and Stacksync keeps Newrelic current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.

What you can sync between Jdbc and Newrelic

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 Newrelic objects How this pairing syncs
Tables The base relational tables in the target database; synced two-way as rows over SQL, with each table's primary key driving upserts and row-level updates. Workloads Workload groupings of related entities via NerdGraph workloadCreate/workloadUpdate/workloadDelete with full CRUD; read for status rollups or provisioned from a service catalog to keep team-level views current. Tables is specific to Jdbc and Workloads to Newrelic — each maps to any object or custom field on the other side.
Views Stored SELECT queries exposed like tables; read-only projections synced outbound when raw base tables should not be exposed downstream. Synthetics Monitors Synthetic uptime and scripted browser checks managed through NerdGraph synthetics mutations (create, update, delete); monitor results are read via NRQL for availability and latency reporting. Views is specific to Jdbc and Synthetics Monitors to Newrelic — 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. Custom Events Custom events posted write-only to the Event API on insights-collector with a License/Ingest key; business or pipeline events pushed into New Relic to enrich dashboards, then queried back out with NRQL. Columns is specific to Jdbc and Custom Events to Newrelic — 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. Change Tracking (Deployments) Deployment and change markers recorded through NerdGraph changeTrackingCreateDeployment; written from CI/CD to annotate charts, and read back via NRQL on the Deployment event for release correlation. Primary keys & indexes is specific to Jdbc and Change Tracking (Deployments) to Newrelic — 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. Dashboards Dashboard definitions and widgets via NerdGraph dashboardCreate/dashboardUpdate/dashboardDelete mutations and entity queries, with full CRUD; exported for backup and audit or provisioned and updated programmatically from a source of truth. Schemas & catalogs is specific to Jdbc and Dashboards to Newrelic — 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. Alert Policies & Conditions Alert policies and NRQL alert conditions managed through NerdGraph alertsPolicy and alertsNrqlCondition mutations with full create, update, and delete; read out for audit or provisioned from a config source so alerting stays consistent across accounts. Stored procedures & functions is specific to Jdbc and Alert Policies & Conditions to Newrelic — each maps to any object or custom field on the other side.

How changes propagate between Jdbc and Newrelic

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 Newrelic 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 Newrelic through its API, with automatic retries and rate-limit backoff.

Newrelic Jdbc Sub-second propagation

DetectionNewrelic notifies Stacksync of record changes through webhook events. NRQL polling over timestamp windows for telemetry (events, metrics, logs, spans).

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.
  • Newrelic: NerdGraph allows 25 concurrent requests per user and returns HTTP 429 when exceeded; NRQL run via APIs is capped at 3,000 queries per account per minute with a 5-second default timeout and about 5,000 data points per response. The Event API accepts 1MB per POST and 100,000 POSTs per minute per account.
What ships with Jdbc ⇄ Newrelic

Connect Jdbc and Newrelic for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Jdbc or Newrelic instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jdbc or Newrelic 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 Newrelic record.

Observability

Monitoring

Track your Jdbc ⇄ Newrelic 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 Newrelic.

How the Jdbc and Newrelic 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.

Newrelic

Integration surface
NerdGraph (GraphQL) plus REST data-ingest APIs (Event, Metric, Log, Trace) and the legacy REST API v2
Authentication
User API key (prefixed NRAK-) sent in the API-Key header for NerdGraph queries and mutations; the data-ingest APIs (Event, Metric, Log) use a License/Ingest key in the Api-Key header. Keys, endpoints, and data are region-scoped (US, EU, JP).
Change detection
NRQL polling over timestamp windows for telemetry (events, metrics, logs, spans); config objects such as dashboards, alert policies, and workloads carry no modified-date and are diffed on each run. Alert workflows can push outbound webhook notifications for near-real-time alerting. No CDC feed.
Capabilities
read · write · webhooks
Rate limits
NerdGraph allows 25 concurrent requests per user and returns HTTP 429 when exceeded; NRQL run via APIs is capped at 3,000 queries per account per minute with a 5-second default timeout and about 5,000 data points per response. The Event API accepts 1MB per POST and 100,000 POSTs per minute per account.
How it works

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

    Choose tables

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

Jdbc and Newrelic 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 310 integrations available for Jdbc and Newrelic.

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