Two-way sync
Changes in Apache Druid or Oracle DB instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Druid 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.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Oracle DB's rows in Apache Druid, 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 Druid in real time, and result tables in Apache Druid sync back into Oracle DB, with schema and type mapping between the two systems handled for you.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in Apache Druid and keep Oracle DB focused on its operational workload.
Rows from Oracle DB land in Apache Druid as they change, replacing hand-built CDC and batch extract jobs.
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 Druid objects | Oracle DB objects | |
|---|---|---|
| Datasources The table-like unit of storage and querying, the main target of reads and ingestion. | Sequences Key generators to respect when external systems insert rows | |
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | PL/SQL procedures and packages In-database logic that can consume or transform synced data | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | Partitions Physical subdivisions relevant when replicating high-volume tables | |
| Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | JSON columns Document data stored in the converged engine and synced alongside relational rows | |
| Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. | Tables The primary read/write surface for row-level sync over SQL | |
| Lookups Key-value mappings joined at query time, refreshable from external systems. | Views Curated read-only projections exposed to downstream consumers |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Oracle DB connection.
Changes in Apache Druid or Oracle DB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Druid or Oracle DB 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 Druid or Oracle DB record.
Track your Apache Druid ⇄ Oracle DB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Druid and Oracle DB.
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 Druid 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.
Pick the Apache Druid 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.
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 Druid and Oracle DB: authenticate both systems, choose the objects to sync (such as Apache Druid's Datasources and Segments), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Apache Druid side: Dimensions, Metrics, Ingestion Supervisors, Lookups, plus custom fields where Apache Druid exposes them. On the Oracle DB side: Sequences, PL/SQL procedures and packages, Partitions, JSON columns. 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 Druid and Oracle DB: Fresh analytics without loading windows; Offload heavy reads; Operational data in the warehouse, minus the pipeline. Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Apache Druid: REST API (SQL over HTTP and native JSON queries); JDBC via Avatica. Authentication: Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy. 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.
Apache Druid: Rollup can pre-aggregate events at ingestion time, meaning the stored granularity may differ from the raw event stream. Oracle DB: The engine is multi-model: relational, JSON, XML, and spatial data live in one database, so a single connection covers mixed data types. Stacksync's field mapping accounts for these differences between Apache Druid and Oracle DB without custom code.
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 Druid and Oracle DB.