Real-time
Two-way sync
Changes in Materialize or Oracle DB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Materialize to Oracle DB integration — real-time, two-way sync
Keep Materialize 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.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Materialize and Oracle DB
Connect Oracle DB and Materialize 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 Materialize, 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 Materialize in real time, and result tables in Materialize sync back into Oracle DB, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Sync operational CRM or ERP data into Materialize so real-time views stay current without batch loads.
- 02 Read computed view results back into a CRM or application database as derived fields.
- 03 Log-based replication of order and inventory tables into an analytics warehouse instead of nightly batch dumps.
- 04 Expose a curated subset of an on-prem Oracle ERP schema to cloud tools by syncing it to a managed Postgres.
Common sync patterns
Serve warehouse results at database speed
Aggregates or model outputs computed in Materialize 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 Materialize and keep Oracle DB focused on its operational workload.
What you can sync between Materialize 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.
| Materialize objects | Oracle DB objects | How this pairing syncs | |
|---|---|---|---|
| Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. | 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. | |
| Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. | Materialized views Precomputed results occasionally used as stable replication sources | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Connections & Secrets Stored credentials and endpoints used by sources and sinks. | JSON columns Document data stored in the converged engine and synced alongside relational rows | Connections & Secrets is specific to Materialize and JSON columns to Oracle DB — each maps to any object or custom field on the other side. | |
| Schemas & Databases Namespaces that organize objects a sync targets. | Views Curated read-only projections exposed to downstream consumers | Schemas & Databases is specific to Materialize and Views to Oracle DB — each maps to any object or custom field on the other side. | |
| Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. | Schemas Per-user namespaces that scope sync permissions and object visibility | Sources is specific to Materialize and Schemas to Oracle DB — each maps to any object or custom field on the other side. | |
| Sinks Outbound connections that emit view changes to Kafka topics. | Sequences Key generators to respect when external systems insert rows | Sinks is specific to Materialize and Sequences to Oracle DB — each maps to any object or custom field on the other side. |
How changes propagate between Materialize 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.
Materialize Oracle DB Sub-second propagation
DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.
DeliveryEach detected change is applied to Oracle DB as a row-level write, with types converted between the two schemas.
Oracle DB Materialize 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 Materialize as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Oracle DB: Throughput bounded by database resources rather than API quotas.
What ships with Materialize ⇄ Oracle DB
Connect Materialize and Oracle DB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Materialize–Oracle DB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Materialize 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 Materialize or Oracle DB record.
Observability
Monitoring
Track your Materialize ⇄ 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 Materialize and Oracle DB.
How the Materialize and Oracle DB connectors work
Materialize
- Integration surface
- PostgreSQL wire protocol (SQL)
- Authentication
- Database credentials (username/password; app passwords in the managed cloud service)
- Change detection
- SUBSCRIBE queries stream row-level changes of any view or table to the client
- Capabilities
- read · write · CDC
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 Materialize 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 Materialize 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.
Materialize
connected
Oracle DB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Materialize 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 · Materialize ⇄ 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.
Materialize Oracle DBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Materialize and Oracle DB integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Materialize and Oracle DB: authenticate both systems, choose the objects to sync (such as Materialize's Tables and Materialized Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Change detection on Materialize: SUBSCRIBE queries stream row-level changes of any view or table to the client. 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.
-
On the Materialize side: Materialized Views, Sinks, Indexes, Clusters, plus custom fields where Materialize 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.
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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.
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Common patterns for Materialize and Oracle DB: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Materialize sync into Oracle DB, where whatever reads from that database gets them without querying the warehouse.
-
Materialize: PostgreSQL wire protocol (SQL). Authentication: Database credentials (username/password; app passwords in the managed cloud service). Oracle DB: 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. Stacksync manages authentication, retries, and rate limits on both sides.
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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