Real-time
Real-time sync
Changes in Databricks or E2 Shop System instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ ERP
Databricks to E2 Shop System integration — real-time data sync
Keep Databricks and E2 Shop System in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from MuleSoft
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Migrated from Celigo
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Databricks and E2 Shop System
Put E2 Shop System's records in Databricks as live tables for reporting and analysis, without extract jobs, and write results back where E2 Shop System can use them.
E2 Shop System is a read-only source: Stacksync reads its data in real time and delivers it into Databricks, so Databricks always reflects the current state of E2 Shop System — without exports, scripts, or schedulers.
ERP data is some of the most asked-for data in the warehouse and some of the hardest to get: the record types are many, the APIs are strict, and extract jobs are brittle. Whether E2 Shop System carries financials, operations, workforce data, or all three, the analysis belongs in Databricks next to everything else the company measures.
Common use cases
- 01 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
- 02 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
- 03 Land quote, job cost, and time-ticket data in a warehouse for margin analysis across jobs.
- 04 Keep purchase order data visible to planning or supplier-facing tools without direct ERP access.
Common sync patterns
Write-back where E2 Shop System exposes writable fields
Classifications or reference values computed in Databricks sync back onto the corresponding records in E2 Shop System.
Where E2 Shop System holds the books: finance reporting from live data
Financial records land in Databricks as they change, so period-end reporting queries current numbers rather than last night's extract.
Where E2 Shop System is the HR system of record: workforce analytics
Worker and organization data syncs into Databricks for headcount, cost, and planning analysis alongside other company data.
What you can sync between Databricks and E2 Shop System
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.
| Databricks objects | E2 Shop System objects | How this pairing syncs | |
|---|---|---|---|
| SQL Warehouses The compute endpoint a sync connects to for query execution. | Vendors Supplier records referenced on purchasing documents. | SQL Warehouses is specific to Databricks and Vendors to E2 Shop System — each maps to any object or custom field on the other side. | |
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Parts Part masters with routings and material definitions specific to each shop. | Change Data Feed is specific to Databricks and Parts to E2 Shop System — each maps to any object or custom field on the other side. | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Routings / Operations Per-part operation sequences that carry estimated and actual times. | Catalogs is specific to Databricks and Routings / Operations to E2 Shop System — each maps to any object or custom field on the other side. | |
| Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Purchase orders Outside material and service purchases tied to jobs. | Schemas is specific to Databricks and Purchase orders to E2 Shop System — each maps to any object or custom field on the other side. | |
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Time tickets Labor collection records used for job costing. | Delta Tables is specific to Databricks and Time tickets to E2 Shop System — each maps to any object or custom field on the other side. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Invoices Billing records synced to accounting for AR reporting. | Views is specific to Databricks and Invoices to E2 Shop System — each maps to any object or custom field on the other side. |
How changes propagate between Databricks and E2 Shop System
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.
Databricks E2 Shop System Sub-second propagation
DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.
DeliveryE2 Shop System does not accept inbound record writes, so this direction carries requests rather than records: E2 Shop System's output flows back as field updates on the originating Databricks records.
E2 Shop System Databricks Interval-based propagation
DetectionStacksync polls E2 Shop System for changes on an incremental schedule, reading only records changed since the previous pass. Polling database tables or scheduled exports.
DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
- E2 Shop System: Not API-bound; constrained by on-premises database access windows.
What ships with Databricks ⇄ E2 Shop System
Connect Databricks and E2 Shop System for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–E2 Shop System connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or E2 Shop System data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single Databricks or E2 Shop System record.
Observability
Monitoring
Track your Databricks ⇄ E2 Shop System sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Databricks and E2 Shop System.
How the Databricks and E2 Shop System connectors work
Databricks
- Integration surface
- SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
- Authentication
- Personal access tokens or OAuth machine-to-machine credentials for service principals
- Change detection
- Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
- Capabilities
- read · write · CDC
- Rate limits
- Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits
E2 Shop System
- Integration surface
- No broadly documented public web API; integration typically works through the underlying database or application import/export, depending on deployment
- Authentication
- Database credentials or application-level export access on the on-premises installation
- Change detection
- Polling database tables or scheduled exports
- Capabilities
- read
- Rate limits
- Not API-bound; constrained by on-premises database access windows
How it works
How to connect Databricks to E2 Shop System — three steps, no code
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.
- 01
Connect your apps
Authenticate Databricks and E2 Shop System with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Databricks
connected
E2 Shop System
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks and E2 Shop System 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.
objects · Databricks ⇄ E2 Shop SystemCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Databricks E2 Shop SystemCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and E2 Shop System integration FAQ
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Yes. Stacksync provides a managed, real-time integration between Databricks and E2 Shop System — E2 Shop System is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
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E2 Shop System is a read-only source, so this integration runs one-way: Stacksync reads from E2 Shop System in real time and delivers into Databricks. Field mapping and monitoring work the same as for two-way pairs.
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Common patterns for Databricks and E2 Shop System: Write-back where E2 Shop System exposes writable fields; Where E2 Shop System holds the books: finance reporting from live data; Where E2 Shop System is the HR system of record: workforce analytics. Classifications or reference values computed in Databricks sync back onto the corresponding records in E2 Shop System.
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Databricks: SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution. Authentication: Personal access tokens or OAuth machine-to-machine credentials for service principals. E2 Shop System: No broadly documented public web API; integration typically works through the underlying database or application import/export, depending on deployment. Authentication: Database credentials or application-level export access on the on-premises installation. Stacksync manages authentication, retries, and rate limits on both sides.
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Databricks: Unity Catalog imposes a three-level namespace (catalog.schema.table) that governs access across workspaces. E2 Shop System: E2 is a Windows-based job shop ERP from Shoptech, now part of ECI Software Solutions, where it has been rebranded as JobBOSS²; most installations run on premises. Stacksync's field mapping accounts for these differences between Databricks and E2 Shop System without custom code.
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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 Databricks and E2 Shop System records are not retained after a sync operation.
SECURITY
Security teams trust Stacksync
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
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E2 Shop System ⇄ Rockset
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