Real-time
Two-way sync
Changes in Elasticsearch or Rockset instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Data warehouse
Elasticsearch to Rockset integration — real-time, two-way sync
Keep Elasticsearch and Rockset 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
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Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from MuleSoft
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Elasticsearch and Rockset
Connect Elasticsearch and Rockset 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 Elasticsearch's rows in Rockset, 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 Rockset in real time, and result tables in Rockset sync back into Elasticsearch, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Serve real-time dashboards over CRM and ERP records synced from operational databases.
- 02 Sync Postgres or DynamoDB tables into collections for low-latency aggregations without loading a batch warehouse.
- 03 Mirror support tickets into an index used for full-text search and agent-assist tooling.
- 04 Feed enriched customer records into an index used for vector or hybrid search in AI applications.
Common sync patterns
Operational data in the warehouse, minus the pipeline
Rows from Elasticsearch land in Rockset as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Rockset sync into Elasticsearch, 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 Elasticsearch and Rockset
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.
| Elasticsearch objects | Rockset objects | How this pairing syncs | |
|---|---|---|---|
| Documents The unit of sync; JSON records created, updated, and deleted by _id. | Documents JSON records addressable by _id, written via the Write API in sync pipelines. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Aliases Stable read/write names that let a sync cut over between index versions without downtime. | Aliases Stable names that point at collections, used to swap datasets without changing queries. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Ingest pipelines Server-side transforms applied to documents as a sync writes them. | Virtual Instances Isolated compute units that separate ingest from query workloads. | Ingest pipelines is specific to Elasticsearch and Virtual Instances to Rockset — each maps to any object or custom field on the other side. | |
| Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | Collections Schemaless document containers that ingested and synced records land in. | Index templates is specific to Elasticsearch and Collections to Rockset — each maps to any object or custom field on the other side. | |
| Indices Target containers for synced records; each holds a table-like collection of JSON documents. | Workspaces Namespaces that group collections and query lambdas per team or environment. | Indices is specific to Elasticsearch and Workspaces to Rockset — each maps to any object or custom field on the other side. | |
| Index mappings Field type definitions that determine how synced fields are indexed and queried. | Query Lambdas Named, parameterized SQL queries invoked over REST to read synced data. | Index mappings is specific to Elasticsearch and Query Lambdas to Rockset — each maps to any object or custom field on the other side. |
How changes propagate between Elasticsearch and Rockset
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.
Elasticsearch Rockset Interval-based propagation
DetectionStacksync polls Elasticsearch for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or sequence fields.
DeliveryEach detected change is applied to Rockset as a row-level write, with types converted between the two schemas.
Rockset Elasticsearch Interval-based propagation
DetectionStacksync polls Rockset for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL queries on timestamp fields.
DeliveryEach detected change is written to Elasticsearch through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Elasticsearch: No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity.
What ships with Elasticsearch ⇄ Rockset
Connect Elasticsearch and Rockset for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–Rockset connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Elasticsearch or Rockset 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 Elasticsearch or Rockset record.
Observability
Monitoring
Track your Elasticsearch ⇄ Rockset sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Elasticsearch and Rockset.
How the Elasticsearch and Rockset connectors work
Elasticsearch
- Integration surface
- REST API (JSON over HTTP)
- Authentication
- API keys or basic authentication; Elastic Cloud also issues service account tokens
- Change detection
- Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
- Capabilities
- read · write
- Rate limits
- No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity
Rockset
- Integration surface
- REST API (SQL over HTTP, plus a document Write API)
- Authentication
- API key
- Change detection
- Polling via SQL queries on timestamp fields; ingestion-side change capture is handled by Rockset's managed source connectors
- Capabilities
- read · write
How it works
How to connect Elasticsearch to Rockset — 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 Elasticsearch and Rockset with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Elasticsearch
connected
Rockset
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Elasticsearch and Rockset 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 · Elasticsearch ⇄ RocksetCustomers 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.
Elasticsearch RocksetCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Elasticsearch and Rockset integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Elasticsearch and Rockset: authenticate both systems, choose the objects to sync (such as Elasticsearch's Documents and Aliases), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Rockset: Rockset was acquired by OpenAI in 2024 and the public service was subsequently wound down, so integrations are relevant mainly for legacy or migration scenarios. Elasticsearch: Writes are addressed by document _id, so upserts map directly onto the index API, and the _bulk endpoint batches many operations in a single request. Stacksync's field mapping accounts for these differences between Elasticsearch and Rockset without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Elasticsearch and Rockset records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Elasticsearch and Rockset connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Elasticsearch–Rockset integration in-house.
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Yes — Stacksync ships production-grade connectors for both Elasticsearch and Rockset. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Elasticsearch: Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks. On Rockset: Polling via SQL queries on timestamp fields; ingestion-side change capture is handled by Rockset's managed source connectors. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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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No integrations match .
