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Data warehouse ⇄ Developer tools

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

Keep Databricks 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 Databricks and Newrelic

Close the gap between analytics and operations: Databricks holds the record while Newrelic runs the day-to-day work, and Stacksync keeps the two in step in real time, in both directions.

Databricks is the central store where teams keep Views, Materialized Views, Volumes, SQL Warehouses for reporting and analysis; Newrelic runs the operational side of engineering work — tracking issues, moving messages and events, watching systems, and managing users and access. The two overlap wherever the same operational data matters to both: the Workloads, Synthetics Monitors, Custom Events, Change Tracking (Deployments) produced in Newrelic are exactly what analysts want to measure in Databricks, and the curated rows in Databricks are what should drive the next action in Newrelic. When that overlap is bridged by nightly ETL or hand-written scripts, dashboards lag a day behind reality and the tools that should react to warehouse signals never see them.

Stacksync syncs Views, Materialized Views, Volumes, SQL Warehouses in Databricks with Workloads, Synthetics Monitors, Custom Events, Change Tracking (Deployments) in Newrelic field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync matches records on a stable external key, keeps every copy consistent, and resolves conflicts by rules you set — so analytics and operations work from the same current data instead of two drifting copies.

Common use cases

  • 01 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • 02 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • 03 Record deployment and change markers from CI/CD through NerdGraph change tracking to correlate releases with performance and error-rate shifts.
  • 04 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.

Common sync patterns

Operational data lands in Databricks for analytics

Records created in Newrelic — issues, events, messages, metrics, or user changes — replicate into Databricks tables as they happen, so reporting runs on current data instead of last night's export.

Warehouse signals reach Newrelic

A row scored, flagged, or enriched in Databricks creates or updates the matching record in Newrelic, so the operational tool acts on the same data the analysts already see.

Backfill history, then stay live

Load the existing set of Workloads, Synthetics Monitors, Custom Events, Change Tracking (Deployments) into Databricks once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.

What you can sync between Databricks 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.

Databricks objects Newrelic objects How this pairing syncs
Schemas Group tables and views; syncs typically target a dedicated schema per source system. 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 is specific to Databricks and Dashboards to Newrelic — each maps to any object or custom field on the other side.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. 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. Delta Tables is specific to Databricks and Alert Policies & Conditions to Newrelic — each maps to any object or custom field on the other side.
Views Curated read-only projections used as sync sources for downstream tools. NRQL Query Results Telemetry events, metrics, logs, and spans queried through NerdGraph's nrql field (or the legacy Insights query API) over time windows; read-only and bounded by data retention, commonly streamed into a warehouse for long-term analysis. Views is specific to Databricks and NRQL Query Results to Newrelic — each maps to any object or custom field on the other side.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Entities The entity catalog of APM applications, hosts, services, and monitors searched via NerdGraph entitySearch; read for inventory, with tags added or replaced through taggingAddTagsToEntity so ownership and environment metadata stay in sync. Materialized Views is specific to Databricks and Entities to Newrelic — each maps to any object or custom field on the other side.
Volumes Unity Catalog file storage used for staging bulk loads. 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. Volumes is specific to Databricks and Workloads to Newrelic — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. 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. SQL Warehouses is specific to Databricks and Synthetics Monitors to Newrelic — each maps to any object or custom field on the other side.

How changes propagate between Databricks 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.

Databricks Newrelic Sub-second propagation

DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.

DeliveryEach detected change is written to Newrelic through its API, with automatic retries and rate-limit backoff.

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

Rate-limit considerations

  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
  • 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 Databricks ⇄ Newrelic

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks 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 Databricks or Newrelic record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Databricks and Newrelic.

How the Databricks and Newrelic connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

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 Databricks 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 Databricks 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
    Databricks connected
    Newrelic connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Databricks 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.

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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 429 integrations available for Databricks and Newrelic.

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