Real-time
Two-way sync
Changes in Apache Pinot or Oracle DB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Apache Pinot to Oracle DB integration — real-time, two-way sync
Keep Apache Pinot and Oracle DB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
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Migrated from Celigo
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Migrated from Matillion
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Apache Pinot and Oracle DB
Connect Oracle DB and Apache Pinot with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Oracle DB'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 Oracle DB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Oracle DB sync into Apache Pinot in real time, and result tables in Apache Pinot sync back into Oracle DB, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Keep upsert-enabled real-time tables aligned with mutable operational records streamed from source systems.
- 02 Query per-account usage metrics from Pinot and sync them into CRM fields so sales sees product activity.
- 03 Expose a curated subset of an on-prem Oracle ERP schema to cloud tools by syncing it to a managed Postgres.
- 04 Keep legacy Oracle applications running while newer services read and write the same data through a synced copy.
Common sync patterns
Serve warehouse results at database speed
Aggregates or model outputs computed in Apache Pinot sync into Oracle DB, where whatever reads from that database gets them without querying the warehouse.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Offload heavy reads
Point analytical queries at the synced copy in Apache Pinot and keep Oracle DB focused on its operational workload.
What you can sync between Apache Pinot and Oracle DB
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 | Oracle DB objects | How this pairing syncs | |
|---|---|---|---|
| Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. | Tables The primary read/write surface for row-level sync over SQL | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | Schemas Per-user namespaces that scope sync permissions and object visibility | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tenants Logical groupings that isolate workloads on shared clusters. | JSON columns Document data stored in the converged engine and synced alongside relational rows | Tenants is specific to Apache Pinot and JSON columns to Oracle DB — each maps to any object or custom field on the other side. | |
| Segments Immutable data files that batch ingestion uploads and the cluster serves. | Views Curated read-only projections exposed to downstream consumers | Segments is specific to Apache Pinot and Views to Oracle DB — 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. | Materialized views Precomputed results occasionally used as stable replication sources | Real-time Tables is specific to Apache Pinot and Materialized views to Oracle DB — 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. | Sequences Key generators to respect when external systems insert rows | Offline Tables is specific to Apache Pinot and Sequences to Oracle DB — each maps to any object or custom field on the other side. |
How changes propagate between Apache Pinot and Oracle DB
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 Oracle DB 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.
DeliveryEach detected change is applied to Oracle DB as a row-level write, with types converted between the two schemas.
Oracle DB Apache Pinot Sub-second propagation
DetectionChanges in Oracle DB are captured at the source via change data capture — no polling loop against its API. Log-based CDC from redo logs via LogMiner or GoldenGate, or trigger and timestamp polling.
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.
- Oracle DB: Throughput bounded by database resources rather than API quotas.
What ships with Apache Pinot ⇄ Oracle DB
Connect Apache Pinot and Oracle DB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–Oracle DB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Pinot or Oracle DB 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 Oracle DB record.
Observability
Monitoring
Track your Apache Pinot ⇄ Oracle DB 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 Oracle DB.
How the Apache Pinot and Oracle DB 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
Oracle DB
- Integration surface
- SQL wire protocol (Oracle Net) via JDBC, ODBC, and native OCI drivers
- Authentication
- database username and password; wallets, Kerberos, and directory-based authentication in enterprise setups
- Change detection
- log-based CDC from redo logs via LogMiner or GoldenGate, or trigger and timestamp polling
- Capabilities
- read · write · CDC
- Rate limits
- throughput bounded by database resources rather than API quotas
How it works
How to connect Apache Pinot to Oracle DB — 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.
- 01
Connect your apps
Authenticate Apache Pinot and Oracle DB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Apache Pinot
connected
Oracle DB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Pinot and Oracle DB 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.
objects · Apache Pinot ⇄ Oracle DBCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Apache Pinot Oracle DBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Pinot and Oracle DB integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Apache Pinot and Oracle DB: authenticate both systems, choose the objects to sync (such as Apache Pinot's Tables and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Apache Pinot and Oracle DB records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Pinot and Oracle DB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Pinot–Oracle DB integration in-house.
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Yes — Stacksync ships production-grade connectors for both Apache Pinot and Oracle DB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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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 Oracle DB: Log-based CDC from redo logs via LogMiner or GoldenGate, or trigger and timestamp polling. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Apache Pinot side: Schemas, Segments, Real-time Tables, Offline Tables, plus custom fields where Apache Pinot exposes them. On the Oracle DB side: Materialized views, Schemas, Sequences, PL/SQL procedures and packages. Stacksync auto-detects both schemas and converts types between the two systems.
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.
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:
Related integrations
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