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Data warehouse ⇄ Developer tools

Apache Hive to Newrelic integration — real-time, two-way sync

Keep Apache Hive 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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Why teams connect Apache Hive and Newrelic

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

Apache Hive is the central store where teams keep ACID Tables, Metastore Catalog, Databases, Managed Tables 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 Dashboards, Alert Policies & Conditions, NRQL Query Results, Entities produced in Newrelic are exactly what analysts want to measure in Apache Hive, and the curated rows in Apache Hive 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 ACID Tables, Metastore Catalog, Databases, Managed Tables in Apache Hive with Dashboards, Alert Policies & Conditions, NRQL Query Results, Entities 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 Publish Hive aggregate tables to a faster serving database for dashboards.
  • 02 Bridge a legacy Hadoop warehouse to a cloud warehouse during migration by syncing tables continuously.
  • 03 Push custom business or pipeline Events and Metrics into New Relic through the Event and Metric APIs so they appear alongside APM data in dashboards and NRQL.
  • 04 Record deployment and change markers from CI/CD through NerdGraph change tracking to correlate releases with performance and error-rate shifts.

Common sync patterns

Backfill history, then stay live

Load the existing set of Dashboards, Alert Policies & Conditions, NRQL Query Results, Entities into Apache Hive once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.

No batch jobs to babysit

New and changed records move field by field the moment they change, replacing scheduled ETL and one-off scripts that fail quietly and leave stale rows behind.

One shared record, kept consistent

Where both systems track the same entity, a change on either side propagates to the other, ending the manual reconciliation between the operational copy and the warehouse copy.

What you can sync between Apache Hive 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.

Apache Hive objects Newrelic objects How this pairing syncs
ACID Tables ORC-backed transactional tables that support row-level insert, update, and delete. 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. ACID Tables is specific to Apache Hive and Entities to Newrelic — each maps to any object or custom field on the other side.
Metastore Catalog The schema registry other engines (Spark, Presto, Impala) also read. 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. Metastore Catalog is specific to Apache Hive and Workloads to Newrelic — each maps to any object or custom field on the other side.
Databases Metastore namespaces that scope tables and grants. 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. Databases is specific to Apache Hive and Synthetics Monitors to Newrelic — each maps to any object or custom field on the other side.
Managed Tables Tables whose data lifecycle Hive controls, used as warehouse destinations. 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. Managed Tables is specific to Apache Hive and Custom Events to Newrelic — each maps to any object or custom field on the other side.
External Tables Tables over existing files in HDFS or object storage, read without moving data. 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. External Tables is specific to Apache Hive and Change Tracking (Deployments) to Newrelic — each maps to any object or custom field on the other side.
Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. 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. Partitions is specific to Apache Hive and Dashboards to Newrelic — each maps to any object or custom field on the other side.

How changes propagate between Apache Hive 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.

Apache Hive Newrelic Interval-based propagation

DetectionStacksync polls Apache Hive for changes on an incremental schedule, reading only records changed since the previous pass. Polling on partition values or timestamp columns.

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

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

Rate-limit considerations

  • Apache Hive: No API quotas; query latency reflects the batch-oriented execution engine underneath.
  • 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 Apache Hive ⇄ Newrelic

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Hive 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 Apache Hive or Newrelic record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Apache Hive and Newrelic connectors work

Apache Hive

Integration surface
SQL (HiveQL) over JDBC/ODBC via HiveServer2 (Thrift)
Authentication
Deployment-dependent: Kerberos, LDAP, or username/password
Change detection
Polling on partition values or timestamp columns; no general-purpose change log for external consumers
Capabilities
read · write
Rate limits
No API quotas; query latency reflects the batch-oriented execution engine underneath

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

    Choose tables

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

Apache Hive 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 319 integrations available for Apache Hive and Newrelic.

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