Real-time
Real-time sync
Changes in Apache Druid or E2 Shop System instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ ERP
Apache Druid to E2 Shop System integration — real-time data sync
Keep Apache Druid 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.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Apache Druid and E2 Shop System
Put E2 Shop System's records in Apache Druid 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 Apache Druid, so Apache Druid 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 Apache Druid next to everything else the company measures.
Common use cases
- 01 Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.
- 02 Expose product telemetry stored in Druid to business tools without granting direct cluster access.
- 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
Group reporting across systems
Combine E2 Shop System's records with data synced from other systems in Apache Druid for consolidated views no single system can produce.
Write-back where E2 Shop System exposes writable fields
Classifications or reference values computed in Apache Druid 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 Apache Druid as they change, so period-end reporting queries current numbers rather than last night's extract.
What you can sync between Apache Druid 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.
| Apache Druid objects | E2 Shop System objects | How this pairing syncs | |
|---|---|---|---|
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | Customers Buyer records synced to CRM or accounting counterparts. | Segments is specific to Apache Druid and Customers to E2 Shop System — each maps to any object or custom field on the other side. | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | Vendors Supplier records referenced on purchasing documents. | Dimensions is specific to Apache Druid and Vendors to E2 Shop System — each maps to any object or custom field on the other side. | |
| Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | Parts Part masters with routings and material definitions specific to each shop. | Metrics is specific to Apache Druid and Parts to E2 Shop System — each maps to any object or custom field on the other side. | |
| Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. | Routings / Operations Per-part operation sequences that carry estimated and actual times. | Ingestion Supervisors is specific to Apache Druid and Routings / Operations to E2 Shop System — each maps to any object or custom field on the other side. | |
| Lookups Key-value mappings joined at query time, refreshable from external systems. | Purchase orders Outside material and service purchases tied to jobs. | Lookups is specific to Apache Druid and Purchase orders to E2 Shop System — each maps to any object or custom field on the other side. | |
| Tasks Batch ingestion and compaction jobs monitored during data loads. | Time tickets Labor collection records used for job costing. | Tasks is specific to Apache Druid and Time tickets to E2 Shop System — each maps to any object or custom field on the other side. |
How changes propagate between Apache Druid 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.
Apache Druid E2 Shop System Interval-based propagation
DetectionStacksync polls Apache Druid for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Druid through streaming or batch ingestion rather than row updates.
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 Apache Druid records.
E2 Shop System Apache Druid 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 Apache Druid as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Apache Druid: No fixed API quotas; query concurrency is bounded by broker and historical node capacity.
- E2 Shop System: Not API-bound; constrained by on-premises database access windows.
What ships with Apache Druid ⇄ E2 Shop System
Connect Apache Druid and E2 Shop System for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–E2 Shop System connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Druid 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 Apache Druid or E2 Shop System record.
Observability
Monitoring
Track your Apache Druid ⇄ 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 Apache Druid and E2 Shop System.
How the Apache Druid and E2 Shop System connectors work
Apache Druid
- Integration surface
- REST API (SQL over HTTP and native JSON queries); JDBC via Avatica
- Authentication
- Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy
- Change detection
- Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates
- Capabilities
- read · write
- Rate limits
- No fixed API quotas; query concurrency is bounded by broker and historical node capacity
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 Apache Druid 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 Apache Druid 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.
Apache Druid
connected
E2 Shop System
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Druid 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 · Apache Druid ⇄ 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.
Apache Druid E2 Shop SystemCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Druid and E2 Shop System integration FAQ
-
Yes. Stacksync provides a managed, real-time integration between Apache Druid 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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On the Apache Druid side: Tasks, Datasources, Segments, Dimensions, plus custom fields where Apache Druid exposes them. On the E2 Shop System side: Invoices, Quotes / Estimates, Jobs / Work orders, Customers. Stacksync auto-detects both schemas and converts types between the two systems.
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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 Apache Druid. Field mapping and monitoring work the same as for two-way pairs.
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Common patterns for Apache Druid and E2 Shop System: Group reporting across systems; Write-back where E2 Shop System exposes writable fields; Where E2 Shop System holds the books: finance reporting from live data. Combine E2 Shop System's records with data synced from other systems in Apache Druid for consolidated views no single system can produce.
-
Apache Druid: REST API (SQL over HTTP and native JSON queries); JDBC via Avatica. Authentication: Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy. 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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Apache Druid: Rollup can pre-aggregate events at ingestion time, meaning the stored granularity may differ from the raw event stream. E2 Shop System: Installations store data in Microsoft Access or Microsoft SQL Server databases depending on size, which is why integrations typically read the database directly. Stacksync's field mapping accounts for these differences between Apache Druid and E2 Shop System without custom code.
SECURITY
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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.
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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
Every pair below is a real-time, two-way sync. Search all 197 integrations available for Apache Druid and E2 Shop System.
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