Two-way sync
Changes in Pinecone or Starburst Enterprise instantly reflect in both systems. No stale data, no manual imports.
Keep Pinecone and Starburst 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.
Starburst Enterprise holds the raw records the business runs on; Pinecone turns those records into embeddings, scores, labels, and summaries. The two meet wherever a warehouse row needs to be enriched by a model and the result needs somewhere durable to live. Most teams stitch that meeting together with export scripts and a queue, then spend their time keeping the glue alive.
Stacksync syncs Index statistics, Indexes, Vectors (records), Namespaces in Pinecone with Schemas, Tables, Views, Materialized views in Starburst Enterprise field by field, in real time, and in both directions. Rows added or changed in Starburst Enterprise flow into Pinecone as they happen, and the Index statistics, Indexes, Vectors (records), Namespaces that Pinecone generates land back in Starburst Enterprise as columns or tables, with field-level mapping and conflict rules in place of a custom pipeline.
The payoff is that model output stops living in a separate place from the data it describes. Once results sit in Starburst Enterprise, they join against billing, product, and usage tables already there, so you can report on quality, cost, and coverage without moving anything by hand.
Scores, labels, embeddings, or summaries produced in Pinecone land in Starburst Enterprise as columns or tables, queryable and joinable with the rest of the business data.
As records change in Starburst Enterprise, matching Index statistics, Indexes, Vectors (records), Namespaces in Pinecone are inserted, updated, or removed, so what Pinecone serves reflects the warehouse instead of a stale snapshot.
Combine Pinecone's output with the tables already in Starburst Enterprise to report on model quality, cost, and coverage without exporting anything to a spreadsheet.
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.
| Pinecone objects | Starburst Enterprise objects | How this pairing syncs | |
|---|---|---|---|
| Vectors (records) The core data: an id (up to 512 chars), a dense values array, optional sparse_values, and JSON metadata (up to 40 KB filterable per record). Full CRUD on the data plane via upsert, update, fetch, query, and delete, so write is supported here. | Catalogs Each catalog maps to a connector (Iceberg, Hive, PostgreSQL, and others) exposing an external source. | Vectors (records) is specific to Pinecone and Catalogs to Starburst Enterprise — each maps to any object or custom field on the other side. | |
| Namespaces Partitions inside an index; every read and write targets one namespace and vectors across namespaces are isolated. Enumerated with list_namespaces and sized per namespace via describe_index_stats. | Schemas Namespaces within a catalog, mirroring the underlying source's databases or schemas. | Namespaces is specific to Pinecone and Schemas to Starburst Enterprise — each maps to any object or custom field on the other side. | |
| Collections Immutable snapshots of a pod-based index that store its data but not its definition; created, listed, and deleted on the control plane and used to recreate a pod-based index. Serverless indexes use Backups instead. | Tables Queryable relations; writes pass through to sources whose connectors support them. | Collections is specific to Pinecone and Tables to Starburst Enterprise — each maps to any object or custom field on the other side. | |
| Backups Point-in-time snapshots of a serverless index; created, listed, and restored into a new index on the control plane for recovery or cloning. Read as a recovery-asset inventory. | Views Engine-level SQL views used to shape federated data before syncing it out. | Backups is specific to Pinecone and Views to Starburst Enterprise — each maps to any object or custom field on the other side. | |
| Index statistics Describe_index_stats returns total and per-namespace vector counts, the index dimension, and index fullness; read to size a sync and to detect drift between Pinecone and the source of truth. | Materialized views Precomputed results that make repeated sync reads cheaper. | Index statistics is specific to Pinecone and Materialized views to Starburst Enterprise — each maps to any object or custom field on the other side. | |
| Indexes Serverless or pod-based containers holding vectors of a fixed dimension and distance metric (cosine, dotproduct, euclidean); managed on the control plane (api.pinecone.io) via create, list, describe, configure, and delete. describe_index returns the per-index data-plane host. | Columns Typed per the Trino type system, mapped from each source's native types. | Indexes is specific to Pinecone and Columns to Starburst Enterprise — each maps to any object or custom field on the other side. |
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.
DetectionStacksync polls Pinecone for changes on an incremental schedule, reading only records changed since the previous pass. No webhooks and no native change-data-capture feed.
DeliveryEach detected change is applied to Starburst Enterprise as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Starburst Enterprise for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling.
DeliveryEach detected change is written to Pinecone through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Pinecone–Starburst Enterprise connection.
Changes in Pinecone or Starburst Enterprise instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Pinecone or Starburst Enterprise data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Pinecone or Starburst Enterprise record.
Track your Pinecone ⇄ Starburst Enterprise sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Pinecone and Starburst Enterprise.
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 Pinecone and Starburst Enterprise 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 Pinecone and Starburst 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.
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 Pinecone and Starburst Enterprise: authenticate both systems, choose the objects to sync (such as Pinecone's Vectors (records) and Namespaces), map fields visually, and changes propagate both ways in milliseconds — no code required.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Pinecone and Starburst Enterprise connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Pinecone–Starburst Enterprise integration in-house.
Yes — Stacksync ships production-grade connectors for both Pinecone and Starburst Enterprise. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Pinecone: No webhooks and no native change-data-capture feed. Vectors carry no server-side update timestamp, so Stacksync detects changes by re-reading - paginating vector ids with the list operation (serverless indexes) and fetching by id, or by re-upserting from the source of truth. describe_index_stats bounds a resync with per-namespace counts. On Starburst Enterprise: Query-based polling; Starburst is a query engine and exposes no change log of its own. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Pinecone side: Index statistics, Indexes, Vectors (records), Namespaces, plus custom fields where Pinecone exposes them. On the Starburst Enterprise side: Schemas, Tables, Views, Materialized views. 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.
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.
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Every pair below is a real-time, two-way sync. Search all 409 integrations available for Pinecone and Starburst Enterprise.