Two-way sync
Changes in Amazon Redshift or Elasticsearch instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon Redshift and Elasticsearch 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 Elasticsearch's rows in Amazon Redshift, 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 Elasticsearch where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Elasticsearch sync into Amazon Redshift in real time, and result tables in Amazon Redshift sync back into Elasticsearch, with schema and type mapping between the two systems handled for you.
Aggregates or model outputs computed in Amazon Redshift sync into Elasticsearch, 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 Amazon Redshift and keep Elasticsearch 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.
| Amazon Redshift objects | Elasticsearch objects | |
|---|---|---|
| Databases Top-level containers within a cluster or serverless workgroup. | Indices Target containers for synced records; each holds a table-like collection of JSON documents. | |
| Schemas Namespaces used to organize synced tables and control grants. | Documents The unit of sync; JSON records created, updated, and deleted by _id. | |
| Tables Columnar tables used as sync destinations for SaaS and database data. | Index mappings Field type definitions that determine how synced fields are indexed and queried. | |
| Views SQL views readable as modeled sources for reverse syncs. | Aliases Stable read/write names that let a sync cut over between index versions without downtime. | |
| Materialized Views Precomputed results that downstream syncs can read for performance. | Data streams Append-only targets for time-series or event data pushed from source systems. | |
| External Tables (Spectrum) S3-backed tables queryable through Redshift, readable in syncs. | Ingest pipelines Server-side transforms applied to documents as a sync writes them. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Redshift–Elasticsearch connection.
Changes in Amazon Redshift or Elasticsearch instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon Redshift or Elasticsearch data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon Redshift or Elasticsearch record.
Track your Amazon Redshift ⇄ Elasticsearch sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon Redshift and Elasticsearch.
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 Amazon Redshift and Elasticsearch 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 Amazon Redshift and Elasticsearch 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 Amazon Redshift and Elasticsearch: authenticate both systems, choose the objects to sync (such as Amazon Redshift's Databases and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Amazon Redshift: Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers. On Elasticsearch: Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Amazon Redshift side: Schemas, Tables, Views, Materialized Views, plus custom fields where Amazon Redshift exposes them. On the Elasticsearch side: Aliases, Data streams, Ingest pipelines, Index templates. 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 Amazon Redshift and Elasticsearch: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Amazon Redshift sync into Elasticsearch, where whatever reads from that database gets them without querying the warehouse.
Amazon Redshift: SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS. Authentication: Database credentials or IAM-based authentication. Elasticsearch: REST API (JSON over HTTP). Authentication: API keys or basic authentication; Elastic Cloud also issues service account tokens. Stacksync manages authentication, retries, and rate limits on both sides.
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 Amazon Redshift and Elasticsearch.