Two-way sync
Changes in Actian Vector or Apache Pinot instantly reflect in both systems. No stale data, no manual imports.
Keep Actian Vector and Apache Pinot 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 Actian Vector and Apache Pinot 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.
| Actian Vector objects | Apache Pinot objects | How this pairing syncs | |
|---|---|---|---|
| Schemas Namespaces used to organize synced tables. | Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tables Columnar tables that serve as sync sources or destinations. | Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views SQL views readable as query-backed sync sources. | Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. | Views is specific to Actian Vector and Real-time Tables to Apache Pinot — each maps to any object or custom field on the other side. | |
| Columns Typed columns mapped field-by-field during schema mapping. | Offline Tables Batch-loaded tables merged with real-time data at query time. | Columns is specific to Actian Vector and Offline Tables to Apache Pinot — each maps to any object or custom field on the other side. | |
| Users and Roles Database principals used to grant the sync connection least-privilege access. | Indexes Inverted, range, and star-tree indexes that determine which sync queries run at low latency. | Users and Roles is specific to Actian Vector and Indexes to Apache Pinot — each maps to any object or custom field on the other side. | |
| Databases Top-level containers targeted by a sync connection. | Tenants Logical groupings that isolate workloads on shared clusters. | Databases is specific to Actian Vector and Tenants to Apache Pinot — 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 Actian Vector for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or key columns.
DeliveryEach detected change is applied to Apache Pinot as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Apache Pinot for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Pinot via streaming ingestion or segment upload, not row-level writes.
DeliveryEach detected change is applied to Actian Vector as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Actian Vector–Apache Pinot connection.
Changes in Actian Vector or Apache Pinot instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Actian Vector or Apache Pinot data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Actian Vector or Apache Pinot record.
Track your Actian Vector ⇄ Apache Pinot sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Actian Vector and Apache Pinot.
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 Actian Vector and Apache Pinot 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 Actian Vector and Apache Pinot 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 Actian Vector and Apache Pinot: authenticate both systems, choose the objects to sync (such as Actian Vector's Schemas and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Actian Vector: SQL over JDBC/ODBC. Authentication: Database credentials. 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. Stacksync manages authentication, retries, and rate limits on both sides.
Actian Vector: Access is through standard SQL over JDBC/ODBC connectivity, which means syncs interact with ordinary tables, views, and schemas. Apache Pinot: Pinot separates offline and real-time tables and merges them at query time through the broker, so one logical table can span batch history and fresh stream data. Stacksync's field mapping accounts for these differences between Actian Vector and Apache Pinot without custom code.
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 Actian Vector and Apache Pinot records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Actian Vector and Apache Pinot connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Actian Vector–Apache Pinot integration in-house.
Yes — Stacksync ships production-grade connectors for both Actian Vector and Apache Pinot. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 199 integrations available for Actian Vector and Apache Pinot.