Two-way sync
Changes in Materialize or Streak CRM instantly reflect in both systems. No stale data, no manual imports.
Keep Materialize and Streak CRM in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.
Stacksync does both with one connection. Stages, Contacts, Organizations, Tasks from Streak CRM land in Materialize as live tables, updated within seconds, and columns computed in Materialize write back to fields in Streak CRM. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Join Streak CRM's relationship data with billing, product, and support data in Materialize to build the customer picture the CRM alone cannot hold.
Deduplication and normalization done in Materialize can be written back, so warehouse-side cleanup actually fixes the CRM.
Accounts, contacts, and activity from Streak CRM are queryable in Materialize moments after they change, so dashboards stop lagging the reality they describe.
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.
| Materialize objects | Streak CRM objects | How this pairing syncs | |
|---|---|---|---|
| Schemas & Databases Namespaces that organize objects a sync targets. | Custom fields Per-pipeline field definitions that determine what data a box can hold. | Schemas & Databases is specific to Materialize and Custom fields to Streak CRM — each maps to any object or custom field on the other side. | |
| Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. | Pipelines Define the process and the custom field schema that boxes in them carry. | Tables is specific to Materialize and Pipelines to Streak CRM — each maps to any object or custom field on the other side. | |
| Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. | Boxes The core record (a deal, hire, or project) tracked through pipeline stages. | Sources is specific to Materialize and Boxes to Streak CRM — each maps to any object or custom field on the other side. | |
| Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. | Stages Pipeline steps whose transitions are the usual trigger for downstream syncs. | Materialized Views is specific to Materialize and Stages to Streak CRM — each maps to any object or custom field on the other side. | |
| Sinks Outbound connections that emit view changes to Kafka topics. | Contacts People linked to boxes, synced with marketing and support tools. | Sinks is specific to Materialize and Contacts to Streak CRM — each maps to any object or custom field on the other side. | |
| Indexes In-memory arrangements that make view reads fast for serving workloads. | Organizations Company records associated with contacts and boxes. | Indexes is specific to Materialize and Organizations to Streak CRM — 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.
DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.
DeliveryEach detected change is written to Streak CRM through its API, with automatic retries and rate-limit backoff.
DetectionStacksync polls Streak CRM for changes on an incremental schedule, reading only records changed since the previous pass. Polling against pipeline, box, and contact endpoints.
DeliveryEach detected change is applied to Materialize as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Materialize–Streak CRM connection.
Changes in Materialize or Streak CRM instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Materialize or Streak CRM data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Materialize or Streak CRM record.
Track your Materialize ⇄ Streak CRM sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Materialize and Streak CRM.
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 Materialize and Streak CRM 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 Materialize and Streak CRM 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 Materialize and Streak CRM: authenticate both systems, choose the objects to sync (such as Materialize's Schemas & Databases and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Streak CRM side: Stages, Contacts, Organizations, Tasks, plus custom fields where Streak CRM exposes them. On the Materialize side: Indexes, Clusters, Connections & Secrets, Schemas & Databases. 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 Materialize and Streak CRM: A single customer view; Cleanup that sticks; CRM analytics on live data. Join Streak CRM's relationship data with billing, product, and support data in Materialize to build the customer picture the CRM alone cannot hold.
Materialize: PostgreSQL wire protocol (SQL). Authentication: Database credentials (username/password; app passwords in the managed cloud service). Streak CRM: REST API. Authentication: API key issued per user. Stacksync manages authentication, retries, and rate limits on both sides.
Streak CRM: Custom fields are defined per pipeline, so two pipelines can have entirely different schemas and sync mappings must be pipeline-aware. Materialize: It ingests CDC from Postgres and MySQL and streams from Kafka as first-class sources. Stacksync's field mapping accounts for these differences between Materialize and Streak CRM 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 354 integrations available for Materialize and Streak CRM.