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Data warehouse ⇄ Analytics

Apache Pinot to Microsoft Power Bi integration — real-time data sync

Keep Apache Pinot and Microsoft Power Bi 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 Pinot and Microsoft Power Bi

Flow Microsoft Power Bi data into Apache Pinot in real time — no exports, no schedulers, no custom scripts.

Microsoft Power Bi is a read-only source: Stacksync reads its data in real time and delivers it into Apache Pinot, so Apache Pinot always reflects the current state of Microsoft Power Bi — without exports, scripts, or schedulers.

Microsoft Power Bi is where teams explore, visualize, and report; Apache Pinot is the store of record that holds the raw tables and full history behind those views. The two overlap wherever the same events, users, and metrics matter to both, and when the bridge between them is a nightly export or a hand-built extract, dashboards lag the warehouse and analysts spend the morning arguing over whose number is right.

Common use cases

  • 01 Pull Dataflow and Datasource definitions to document lineage between Power BI and its upstream warehouses in a governance database.
  • 02 Load dataset Refresh History into an operational database to alert on-call teams when scheduled refreshes fail or run long.
  • 03 Query per-account usage metrics from Pinot and sync them into CRM fields so sales sees product activity.
  • 04 Push reference and dimension data into Pinot via batch segment loads to enrich event queries.

Common sync patterns

One number both sides agree on

Metrics and aggregates stay aligned between the two systems, so a figure shown in Microsoft Power Bi matches the Apache Pinot table it was built from instead of drifting between refreshes.

Where Apache Pinot holds the source tables: live data in the reporting layer

Records maintained in Apache Pinot flow into Microsoft Power Bi as they change, so dashboards and reports read current rows rather than an overnight extract.

Where Microsoft Power Bi produces segments or scores: results back to the warehouse

Cohorts, segments, and computed metrics defined in Microsoft Power Bi write to Apache Pinot as tables the rest of the stack can query and join.

What you can sync between Apache Pinot and Microsoft Power Bi

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 Pinot objects Microsoft Power Bi objects How this pairing syncs
Tenants Logical groupings that isolate workloads on shared clusters. Dashboards and Tiles Dashboards and their pinned tiles read via GET /dashboards and /dashboards/{id}/tiles; inventoried to map dashboard content back to its source datasets. Tenants is specific to Apache Pinot and Dashboards and Tiles to Microsoft Power Bi — each maps to any object or custom field on the other side.
Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. Dataflows Power Query ETL definitions read via GET /groups/{id}/dataflows; used to document lineage from upstream sources into datasets. Tables is specific to Apache Pinot and Dataflows to Microsoft Power Bi — each maps to any object or custom field on the other side.
Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. Datasources and Gateways The connections behind datasets and dataflows and the on-premises gateways serving them, read via REST for lineage and dependency mapping. Schemas is specific to Apache Pinot and Datasources and Gateways to Microsoft Power Bi — each maps to any object or custom field on the other side.
Segments Immutable data files that batch ingestion uploads and the cluster serves. Refresh History Dataset refresh runs read via GET /datasets/{id}/refreshes, including status, type, and timing, to alert on failed or slow scheduled refreshes. Segments is specific to Apache Pinot and Refresh History to Microsoft Power Bi — each maps to any object or custom field on the other side.
Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. Workspaces (Groups) Containers for content read via GET /groups (tenant-wide via GET /admin/groups); mirrored to reproduce the tenant's content hierarchy in a catalog. Real-time Tables is specific to Apache Pinot and Workspaces (Groups) to Microsoft Power Bi — each maps to any object or custom field on the other side.
Offline Tables Batch-loaded tables merged with real-time data at query time. Activity Events (Audit Log) Admin audit log of user and content actions read via GET /admin/activityevents; loaded for security, access, and usage reporting across the tenant. Offline Tables is specific to Apache Pinot and Activity Events (Audit Log) to Microsoft Power Bi — each maps to any object or custom field on the other side.

How changes propagate between Apache Pinot and Microsoft Power Bi

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 Pinot Microsoft Power Bi Interval-based propagation

DetectionStacksync polls Apache Pinot for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Pinot via streaming ingestion or segment upload, not row-level writes.

DeliveryMicrosoft Power Bi does not accept inbound record writes, so this direction carries requests rather than records: Microsoft Power Bi's output flows back as field updates on the originating Apache Pinot records.

Microsoft Power Bi Apache Pinot Interval-based propagation

DetectionStacksync polls Microsoft Power Bi for changes on an incremental schedule, reading only records changed since the previous pass. Pull-based: no webhooks or change-data-capture.

DeliveryEach detected change is applied to Apache Pinot as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Apache Pinot: No fixed API quotas; query throughput depends on broker and server sizing.
  • Microsoft Power Bi: Endpoints throttle per user and per app and return HTTP 429 with a Retry-After header. Execute Queries allows up to 120 requests per minute per user and caps a query at 100,000 rows (or 1,000,000 values) and 15 MB; admin scanner metadata APIs are limited to about 500 requests per hour with 16 concurrent.
What ships with Apache Pinot ⇄ Microsoft Power Bi

Connect Apache Pinot and Microsoft Power Bi for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–Microsoft Power Bi connection.

Real-time

Real-time sync

Changes in Apache Pinot or Microsoft Power Bi instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Pinot or Microsoft Power Bi 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 Pinot or Microsoft Power Bi record.

Observability

Monitoring

Track your Apache Pinot ⇄ Microsoft Power Bi sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Pinot and Microsoft Power Bi.

How the Apache Pinot and Microsoft Power Bi connectors work

Apache Pinot

Integration surface
REST API (SQL queries via the broker; administration via the controller); JDBC client available
Authentication
Deployment-dependent: HTTP basic authentication or token-based auth where enabled
Change detection
Not applicable for reads out (polling by time column); data enters Pinot via streaming ingestion or segment upload, not row-level writes
Capabilities
read · write
Rate limits
No fixed API quotas; query throughput depends on broker and server sizing

Microsoft Power Bi

Integration surface
Power BI REST API, including the Execute Queries (DAX) endpoint and admin scanner APIs; a read-write XMLA endpoint is available on Premium, Premium-Per-User, and Fabric capacity.
Authentication
Microsoft Entra ID (Azure AD) OAuth 2.0 bearer tokens. Supports delegated user tokens and app-only service principals; service principals must be enabled under the tenant's Developer settings and granted workspace access. Tenant-wide admin reads require the Tenant.Read.All scope.
Change detection
Pull-based: no webhooks or change-data-capture. Content is polled via REST list endpoints, dataset changes are inferred from Refresh History and the admin Activity Events audit log, and the scanner API's GetModifiedWorkspaces reports workspaces changed since a given time.
Capabilities
read
Rate limits
Endpoints throttle per user and per app and return HTTP 429 with a Retry-After header. Execute Queries allows up to 120 requests per minute per user and caps a query at 100,000 rows (or 1,000,000 values) and 15 MB; admin scanner metadata APIs are limited to about 500 requests per hour with 16 concurrent.
How it works

How to connect Apache Pinot to Microsoft Power Bi — 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 Pinot and Microsoft Power Bi 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 Pinot connected
    Microsoft Power Bi connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Pinot and Microsoft Power Bi 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 Pinot ⇄ Microsoft Power Bi
    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 Pinot Microsoft Power Bi
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Apache Pinot and Microsoft Power Bi integration FAQ

SECURITY

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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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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

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Related integrations

Every pair below is a real-time, two-way sync. Search all 369 integrations available for Apache Pinot and Microsoft Power Bi.

Popular · 7 of 369
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