Two-way sync
Changes in Rockset or Yellowbrick instantly reflect in both systems. No stale data, no manual imports.
Keep Rockset and Yellowbrick in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.
Stacksync syncs tables between Rockset and Yellowbrick continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
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.
| Rockset objects | Yellowbrick objects | |
|---|---|---|
| Query Lambdas Named, parameterized SQL queries invoked over REST to read synced data. | Views Logical views used to shape reads for BI and downstream syncs. | |
| Aliases Stable names that point at collections, used to swap datasets without changing queries. | Users and Roles Access-control objects that govern what a sync service account can read and write. | |
| Integrations Managed source connections (databases, streams, object storage) feeding collections. | Databases Top-level containers for schemas and tables. | |
| Virtual Instances Isolated compute units that separate ingest from query workloads. | Schemas Namespaces used to organize synced datasets by source or domain. | |
| Collections Schemaless document containers that ingested and synced records land in. | Tables Columnar MPP tables; the primary targets for warehouse syncs. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Rockset–Yellowbrick connection.
Changes in Rockset or Yellowbrick instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Rockset or Yellowbrick data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Rockset or Yellowbrick record.
Track your Rockset ⇄ Yellowbrick sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Rockset and Yellowbrick.
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 Rockset and Yellowbrick 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 Rockset and Yellowbrick 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 Rockset and Yellowbrick: authenticate both systems, choose the objects to sync (such as Rockset's Query Lambdas and Aliases), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Rockset side: Aliases, Integrations, Virtual Instances, Collections, plus custom fields where Rockset exposes them. On the Yellowbrick side: Schemas, Tables, Views, Users and Roles. 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 Rockset and Yellowbrick: Serve tools that only connect to one platform; Shared datasets across teams; Consolidation after M&A. Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
Rockset: REST API (SQL over HTTP, plus a document Write API). Authentication: API key. Yellowbrick: SQL wire protocol (PostgreSQL-compatible) with JDBC/ODBC drivers; bulk loading via the ybload utility. Authentication: Database credentials, with LDAP and Kerberos options in enterprise deployments. Stacksync manages authentication, retries, and rate limits on both sides.
Rockset: Ingest is schemaless: JSON documents are indexed as-is with dynamic typing, so upstream schema drift does not break the pipeline. Yellowbrick: The front end is PostgreSQL-compatible, so standard Postgres drivers and SQL tooling connect without custom clients. Stacksync's field mapping accounts for these differences between Rockset and Yellowbrick 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 Rockset and Yellowbrick.