Two-way sync
Changes in Cloudera Data Platform or Redis Enterprise instantly reflect in both systems. No stale data, no manual imports.
Keep Cloudera Data Platform and Redis Enterprise 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 Redis Enterprise's rows in Cloudera Data Platform, 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 Redis Enterprise where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Redis Enterprise sync into Cloudera Data Platform in real time, and result tables in Cloudera Data Platform sync back into Redis Enterprise, with schema and type mapping between the two systems handled for you.
Aggregates or model outputs computed in Cloudera Data Platform sync into Redis Enterprise, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in Cloudera Data Platform and keep Redis Enterprise focused on its operational workload.
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.
| Cloudera Data Platform objects | Redis Enterprise objects | |
|---|---|---|
| Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Hashes Field-value maps that commonly hold one synced row per hash, keyed by record ID. | |
| Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | JSON documents Native JSON storage (RedisJSON) for nested records synced from APIs or document stores. | |
| Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Sets Unordered unique-member collections used for membership checks like segment or ID lists. | |
| Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | Sorted Sets Score-ordered collections used for rankings, priority queues, and time-ordered indexes. | |
| Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. | Lists Ordered sequences often used as lightweight queues fed by sync events. | |
| Views SQL views that can present curated, sync-ready projections of raw lake data. | Streams Append-only logs with consumer groups, used to fan sync events out to downstream services. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cloudera Data Platform–Redis Enterprise connection.
Changes in Cloudera Data Platform or Redis Enterprise instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Cloudera Data Platform or Redis Enterprise data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Cloudera Data Platform or Redis Enterprise record.
Track your Cloudera Data Platform ⇄ Redis Enterprise sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Cloudera Data Platform and Redis Enterprise.
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 Cloudera Data Platform and Redis Enterprise 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 Cloudera Data Platform and Redis Enterprise 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 Cloudera Data Platform and Redis Enterprise: authenticate both systems, choose the objects to sync (such as Cloudera Data Platform's Databases and Hive tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Cloudera Data Platform side: Object store / HDFS files, Databases, Hive tables, Impala tables, plus custom fields where Cloudera Data Platform exposes them. On the Redis Enterprise side: JSON documents, Sets, Sorted Sets, Lists. 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 Cloudera Data Platform and Redis Enterprise: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Cloudera Data Platform sync into Redis Enterprise, where whatever reads from that database gets them without querying the warehouse.
Cloudera Data Platform: JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs. Authentication: Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway. Redis Enterprise: Redis wire protocol (RESP) via client libraries; separate REST API for cluster management. Authentication: Password or ACL-based credentials, typically over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
Cloudera Data Platform: Tables can live in multiple storage engines with different update semantics: Kudu and Iceberg tables support row-level updates, while classic Hive tables are append-oriented. Redis Enterprise: Redis Enterprise adds clustering, tiered storage, and Active-Active geo-replication (CRDT-based) on top of open-source Redis. Stacksync's field mapping accounts for these differences between Cloudera Data Platform and Redis Enterprise 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 Cloudera Data Platform and Redis Enterprise.