Two-way sync
Changes in Apache Pinot or Snowflake instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Pinot and Snowflake 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 Apache Pinot and Snowflake 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.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
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.
| Apache Pinot objects | Snowflake objects | |
|---|---|---|
| Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | Tables The main landing and activation target for synced records. | |
| Segments Immutable data files that batch ingestion uploads and the cluster serves. | Views Modeled projections used as the source side of outbound syncs. | |
| Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. | Materialized Views Precomputed results synced outward for low-latency reads. | |
| Offline Tables Batch-loaded tables merged with real-time data at query time. | Streams Row-level change records on a table, consumed to process deltas instead of full scans. | |
| Indexes Inverted, range, and star-tree indexes that determine which sync queries run at low latency. | Stages File staging areas used for bulk loads into synced tables. | |
| Tenants Logical groupings that isolate workloads on shared clusters. | Tasks Scheduled SQL used to transform synced data after it lands. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–Snowflake connection.
Changes in Apache Pinot or Snowflake instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Pinot or Snowflake data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Pinot or Snowflake record.
Track your Apache Pinot ⇄ Snowflake sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Pinot and Snowflake.
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 Apache Pinot and Snowflake 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 Apache Pinot and Snowflake 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 Apache Pinot and Snowflake: authenticate both systems, choose the objects to sync (such as Apache Pinot's Schemas and Segments), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Apache Pinot side: Offline Tables, Indexes, Tenants, Tables, plus custom fields where Apache Pinot exposes them. On the Snowflake side: Tables, Views, Materialized Views, Streams. 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 Apache Pinot and Snowflake: Consolidation after M&A; Migration without a big bang; Serve tools that only connect to one platform. Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
Apache Pinot: REST API (SQL queries via the broker; administration via the controller); JDBC client available. Authentication: Deployment-dependent: HTTP basic authentication or token-based auth where enabled. Snowflake: SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API. Authentication: Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles. Stacksync manages authentication, retries, and rate limits on both sides.
Apache Pinot: The star-tree index pre-aggregates along configured dimensions, trading storage for consistently low query latency. Snowflake: Compute runs on virtual warehouses that are billed and scaled separately from storage, so sync workloads can be isolated on their own warehouse. Stacksync's field mapping accounts for these differences between Apache Pinot and Snowflake 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 Apache Pinot and Snowflake.