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Data warehouse ⇄ Database

Databricks to Redis Enterprise integration — real-time, two-way sync

Keep Databricks 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.

  • 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

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Why teams connect Databricks and Redis Enterprise

Connect Redis Enterprise and Databricks 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 Redis Enterprise's rows in Databricks, 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 Databricks in real time, and result tables in Databricks sync back into Redis Enterprise, with schema and type mapping between the two systems handled for you.

Common use cases

  • Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • Sync Postgres reference tables into RedisJSON documents that power API responses and personalization lookups.
  • Publish record-change events into Redis Streams so microservices react to upstream CRM updates without polling.

Operational data in the warehouse, minus the pipeline

Rows from Redis Enterprise land in Databricks as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Databricks sync into Redis Enterprise, 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.

What you can sync between Databricks and Redis Enterprise

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.

Databricks objects Redis Enterprise objects
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Pub/Sub channels Fire-and-forget messaging used to notify applications when synced keys change.
Views Curated read-only projections used as sync sources for downstream tools. Search indexes Secondary indexes (RediSearch) that make synced hashes and JSON documents queryable.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Keys (Strings) Simple key-value pairs used to cache individual synced records or lookup values.
Volumes Unity Catalog file storage used for staging bulk loads. Hashes Field-value maps that commonly hold one synced row per hash, keyed by record ID.
SQL Warehouses The compute endpoint a sync connects to for query execution. JSON documents Native JSON storage (RedisJSON) for nested records synced from APIs or document stores.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Sets Unordered unique-member collections used for membership checks like segment or ID lists.
What ships with Databricks ⇄ Redis Enterprise

Connect Databricks and Redis Enterprise for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Redis Enterprise connection.

Real-time

Two-way sync

Changes in Databricks or Redis Enterprise instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Redis Enterprise 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 Databricks or Redis Enterprise record.

Observability

Monitoring

Track your Databricks ⇄ Redis Enterprise sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Databricks and Redis Enterprise.

How the Databricks and Redis Enterprise connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

Redis Enterprise

Integration surface
Redis wire protocol (RESP) via client libraries; separate REST API for cluster management
Authentication
Password or ACL-based credentials, typically over TLS
Change detection
Keyspace notifications over pub/sub or reads from Redis Streams; no transaction-log CDC surface for data
Capabilities
read · write
Rate limits
Throughput is bounded by provisioned cluster capacity rather than published API rate limits
How it works

How to connect Databricks to Redis Enterprise — 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.

  1. 01

    Connect your apps

    Authenticate Databricks 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Databricks connected
    Redis Enterprise connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Databricks ⇄ Redis Enterprise
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Databricks Redis Enterprise
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Databricks and Redis Enterprise integration FAQ

SECURITY

Security teams love 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
CSA STAR
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

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Databricks and Redis Enterprise.

Popular · 8 of 386
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