Two-way sync
Changes in Apache Pinot or Azure SQL Database instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Pinot and Azure SQL Database in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Azure SQL Database's rows in Apache Pinot, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Azure SQL Database where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Azure SQL Database sync into Apache Pinot in real time, and result tables in Apache Pinot sync back into Azure SQL Database, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Apache Pinot and keep Azure SQL Database focused on its operational workload.
Rows from Azure SQL Database land in Apache Pinot as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Apache Pinot sync into Azure SQL Database, where whatever reads from that database gets them without querying the warehouse.
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 | Azure SQL Database objects | |
|---|---|---|
| Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | Change tracking / CDC tables System-maintained change records used to drive incremental sync. | |
| Segments Immutable data files that batch ingestion uploads and the cluster serves. | Tables The primary sync target; rows map one-to-one to records in the paired system. | |
| Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. | Views Read-only projections used when the sync should expose a curated shape rather than raw tables. | |
| Offline Tables Batch-loaded tables merged with real-time data at query time. | Schemas Namespaces that organize tables and control which objects a sync user can reach. | |
| Indexes Inverted, range, and star-tree indexes that determine which sync queries run at low latency. | Rows and columns Standard relational records with typed columns; primary keys anchor upserts. | |
| Tenants Logical groupings that isolate workloads on shared clusters. | Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–Azure SQL Database connection.
Changes in Apache Pinot or Azure SQL Database instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Pinot or Azure SQL Database data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Pinot or Azure SQL Database record.
Track your Apache Pinot ⇄ Azure SQL Database sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Pinot and Azure SQL Database.
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.
Authenticate Apache Pinot and Azure SQL Database with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Apache Pinot and Azure SQL Database 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Apache Pinot and Azure SQL Database: authenticate both systems, choose the objects to sync (such as Apache Pinot's Schemas and Segments), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Apache Pinot: Not applicable for reads out (polling by time column); data enters Pinot via streaming ingestion or segment upload, not row-level writes. On Azure SQL Database: Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Pinot side: Tables, Schemas, Segments, Real-time Tables, plus custom fields where Apache Pinot exposes them. On the Azure SQL Database side: Stored procedures, Change tracking / CDC tables, Tables, Views. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Apache Pinot and Azure SQL Database: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Apache Pinot and keep Azure SQL Database focused on its operational workload.
Apache Pinot: 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. Azure SQL Database: SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers. Authentication: SQL authentication (database credentials) or Microsoft Entra ID authentication. Stacksync manages authentication, retries, and rate limits on both sides.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Pinot and Azure SQL Database.