Sienge Connector: sync your construction management data directly to your warehouse without maintaining pipelines
Managed Sienge connector for BigQuery, Redshift, and PostgreSQL. Sync financial data, construction sites, contracts, and over 90 endpoints with zero pipeline code. Erathos.
Managed connector to sync financial, accounting, construction, sales contracts, accounts receivable, inventory data, and more from Sienge to BigQuery, Redshift, and PostgreSQL. Create your account and test it now.
Every data team serving a construction company or real estate developer eventually hits the same roadblock: operational data lives in Sienge, the rest of the analytical stack lives in the data warehouse, and joining the two becomes an engineering project that nobody planned for. What starts as a Python script running on an EC2 cron job transforms three months later into a pipeline that nobody understands, fails silently, and no engineer wants to inherit.
Erathos launches the managed connector for Sienge. More than ninety endpoints available, covering finance, accounting, construction progress, contracts, inventory, and sales. Zero pipeline code to write or maintain.
The problem with custom-built Sienge pipelines
The Sienge API is authenticated via username and password, with the account's subdomain varying per tenant. The pattern is simple enough to convince any engineer to build an in-house integration in an afternoon. The real cost appears later, and it's predictable.
Pagination with different behavior per module
Accounts receivable, inventory movements, ledger entries, and sales contract endpoints have distinct volumes and pagination behaviors. The logic that works for one module doesn't necessarily work for another, and when Sienge adjusts a default page size or changes the cursor, the pipeline stops bringing in all records without raising an error.
Rate limit handling during backfills
In a normal incremental extract, for medium-sized volumes, the pipeline stays below the limit. In a historical backfill of ledger entries or accounts receivable installments, the volume of requests spikes quickly. If retry logic is not properly implemented with exponential backoff, entire data windows are lost without warning.
Silent schema evolution
Sienge covers an extensive domain: finance, accounting, procurement, construction, sales. New fields appear with new modules or platform updates. The dbt model that used to run clean begins to fail in production, or worse: it keeps running, but with a coalesce on a field that disappeared. The inconsistency ends up in the construction cost report before it hits the data monitoring system.
No observability
A 200 OK on an HTTP call doesn't mean the data arrived correctly. Without record counts per endpoint per run, comparison with the previous window, and volume drop alerts, you are flying blind. The pipeline that ran successfully could have fetched zero new installments because the cursor got stuck.
The worst-case scenario isn't the pipeline that breaks and sends an alert. It's the pipeline that executes successfully and delivers incorrect data, so the cash flow report that finance opens on Monday morning is already calculated on top of a broken base.
What is possible once Sienge data reaches the warehouse
Cash flow and delinquency analysis with joined data
With accounts_receivable_receivable_bills and accounts_receivable_receivable_bill_installments in the warehouse, it is possible to calculate delinquency positions by development project, customer type, and due date with record-level precision—not as aggregated exports from the Sienge dashboard. By joining this with customers and enterprises, you can answer questions like: which projects concentrate the highest exposure of overdue receivables? Which customer types have the highest renegotiation rate?
Construction cost control on a cost-center and materials level
With bills, bills_budget_categories, bills_buildings_cost, and bills_departments_cost in the warehouse, you can build a view of budget commitment per project and per cost center at the entry level. Unlike Sienge's native reports, which are pre-aggregated by period, here you have the raw data to build any analysis dimension the controller needs.
Budget vs. actual comparisons for construction estimates
The endpoints building_cost_estimations_sheets, building_cost_estimations_resources, and building_cost_estimations_cost_estimate_resources bring in the analytic cost structure of the planned project. Alongside actual expenses in bills and daily construction logs in construction_daily_report, you can model cost variance per project phase and material group—a model that doesn't exist natively in any Sienge dashboard.
Portfolio analysis of sales contracts and receivables
With sales_contracts, units, enterprises, and price_tables in the warehouse, you can construct a portfolio sales view per project, highlighting contract stages, contracted values, indexation, and collection projections. Joining this with accounts_receivable_receivable_bill_installments closes the loop between signed contracts and actual cash collection positions.
Inventory management and material tracking
The endpoints inventory_movements, stock_reservations, and stock_inventories_items bring the historical ledger of inventory movements per project. With this in the warehouse, you can identify consumption per stage, variances against planned schedules, and cross-reference with quotation and purchase data from purchase_quotations_negotiations and purchase_requests_items.
Multi-company consolidation for accounting
With accountancy_entries, accountancy_accounts, accounts_balances, and companies in the warehouse, the controller managing multiple companies within the same group can consolidate the chart of accounts and balances into a single analytical model without needing to export reports from each company individually.
What is available in the connector
The Sienge connector delivers more than ninety endpoints ready to be materialized in the destination warehouse, covering the main platform modules:
Finance and Accounting
Endpoint | What it contains |
|---|---|
| Chart of accounts |
| Ledger entries |
| Automatic entries batches |
| Automatic entry logs |
| Batch entry items |
| Balances per account |
| Account statements |
| Accounting batches |
| Checking accounts |
| Accounting closures |
| Account balance (bulk) |
| Balance by account and cost center (bulk) |
| Bank movements (bulk) |
| Revenues (bulk) |
| Expenses (bulk) |
Accounts Receivable
Endpoint | What it contains |
|---|---|
| Invoices and bills receivable |
| Receivable installments |
| Budget categories of receivables |
| Receivables custodians |
| Customer debt balance (bulk) |
| Customer statement history (bulk) |
| Defaulters (bulk) |
| Defaulters by aging (bulk) |
Accounts Payable
Endpoint | What it contains |
|---|---|
| Accounts payable |
| Accounts payable by change date |
| Accounts payable installments |
| Taxes on accounts payable |
| Budget categories |
| Costs by department |
| Costs by project |
| Accounts payable attachments |
| Units linked to bills |
| Electronic invoices (NF-e) |
| NF-e payments |
| Linked NF-e |
Projects and Budgets
Endpoint | What it contains |
|---|---|
| Cost estimation spreadsheets |
| Estimate resources |
| Resource movement units |
| Cost estimate resources |
| Non-working days per project |
| Project progress logs |
| Daily construction log |
| Daily log event types |
| Daily construction log types |
| Estimate items (bulk) |
| Project resources (bulk) |
| Business budget (bulk) |
Sales Contracts and Units
Endpoint | What it contains |
|---|---|
| Sales contracts |
| Contract attachments |
| Contract guarantors |
| Real estate units |
| Unit features |
| Unit statuses |
| Real estate map |
| Property leasing |
| Property types |
| Sales (bulk) |
| Commissions |
| Commission settings by broker |
| Sales commissions |
| Price tables |
| Correction indices |
Inventory and Procurement
Endpoint | What it contains |
|---|---|
| Inventory ledger |
| Inventory reservations |
| Inventory item lists |
| Quote negotiations |
| Purchase request items |
| Quotations (bulk) |
| Supply contract measurements |
| Measurement items |
| Measurement attachments |
| Cost databases |
| Cost database resources |
| Cost database service items |
| Service item compositions |
Registries and Settings
Endpoint | What it contains |
|---|---|
| Companies |
| Projects/Enterprises |
| Customers |
| Customer attachments |
| Creditors |
| Creditor bank details |
| Creditor Pix details |
| Cost centers |
| Departments |
| Jobsites/sites |
| Cities |
| Marital status |
| Customer types |
| Payment terms types |
| Fixed assets |
| Movable assets |
| Professions |
| Resource groups |
| Trademarks |
| Units of measure |
| Service item groups |
| Invoice items (bulk) |
Supported destinations: BigQuery, Redshift, and PostgreSQL.
How to authenticate
Connector authentication requires three fields:
Subdomain: the Sienge account subdomain (the identifier in the API URLs, for example:
mycompany)User: the Sienge user's email address (for example:
your@email.com)Password: the Sienge user's password
Full documentation: docs.erathos.com/connectors/apis/sienge
Why outsource ingestion to Erathos
The conector premise is straightforward: maintaining ingestion pipelines shouldn't be the data team's responsibility. Pagination, rate limits, exponential backoff retries, schema evolution, failure reports, volume drop alerts, and backfills are all handled by the ingestion platform.
Once configured, the platform delivers:
End-to-end visibility of every run
Extraction time per endpoint, record counts per window, which windows were processed, and where retries occurred. When the construction cost report changes on the dashboard and the controller opens a ticket for the data team, there is a full tracing history to find the root cause.
Out-of-the-box alerting
Execution failures, volume drops per endpoint, and window delay flags are detected and routed via the alerting integrations your team already uses. No need to write that code.
Reprocessing as a platform operation
When you need to reprocess a window—either because the dbt model changed or a source correction arrived—it is handled as a simple platform operation, not an improvised sequence of DELETE + INSERT queries inside your warehouse.
Correct pagination, rate limit handling, schema evolution, and backfills are platform responsibilities. The data team focuses on modelling, not plumbing.
Available pipelines
Sienge to BigQuery: https://www.erathos.com/pipelines/sienge-bigquery
Sienge to Redshift: https://www.erathos.com/pipelines/sienge-redshift
Sienge to PostgreSQL: https://www.erathos.com/pipelines/sienge-postgresql
Sienge to Databricks: https://www.erathos.com/pipelines/sienge-databricks
Sienge to Azure SQL Server: https://www.erathos.com/pipelines/sienge-azure-sql-server
Sienge to Supabase: https://www.erathos.com/pipelines/sienge-supabase
Sienge to Amazon S3: https://www.erathos.com/pipelines/sienge-amazon-s3
Get started
Create your account on Erathos and connect Sienge to your warehouse in minutes. With your subdomain, username, and password, your first data loads will land without writing, maintaining, or monitoring a single line of pipeline code.
Daily construction, contract, financial, and inventory data shouldn't be locked inside an ERP, disconnected from the rest of your analytical model. Or worse, in a home-grown pipeline that will drain your team's attention month after month forever.
See the full connector documentation at docs.erathos.com/connectors/apis/sienge.
Managed connector to sync financial, accounting, construction, sales contracts, accounts receivable, inventory data, and more from Sienge to BigQuery, Redshift, and PostgreSQL. Create your account and test it now.
Every data team serving a construction company or real estate developer eventually hits the same roadblock: operational data lives in Sienge, the rest of the analytical stack lives in the data warehouse, and joining the two becomes an engineering project that nobody planned for. What starts as a Python script running on an EC2 cron job transforms three months later into a pipeline that nobody understands, fails silently, and no engineer wants to inherit.
Erathos launches the managed connector for Sienge. More than ninety endpoints available, covering finance, accounting, construction progress, contracts, inventory, and sales. Zero pipeline code to write or maintain.
The problem with custom-built Sienge pipelines
The Sienge API is authenticated via username and password, with the account's subdomain varying per tenant. The pattern is simple enough to convince any engineer to build an in-house integration in an afternoon. The real cost appears later, and it's predictable.
Pagination with different behavior per module
Accounts receivable, inventory movements, ledger entries, and sales contract endpoints have distinct volumes and pagination behaviors. The logic that works for one module doesn't necessarily work for another, and when Sienge adjusts a default page size or changes the cursor, the pipeline stops bringing in all records without raising an error.
Rate limit handling during backfills
In a normal incremental extract, for medium-sized volumes, the pipeline stays below the limit. In a historical backfill of ledger entries or accounts receivable installments, the volume of requests spikes quickly. If retry logic is not properly implemented with exponential backoff, entire data windows are lost without warning.
Silent schema evolution
Sienge covers an extensive domain: finance, accounting, procurement, construction, sales. New fields appear with new modules or platform updates. The dbt model that used to run clean begins to fail in production, or worse: it keeps running, but with a coalesce on a field that disappeared. The inconsistency ends up in the construction cost report before it hits the data monitoring system.
No observability
A 200 OK on an HTTP call doesn't mean the data arrived correctly. Without record counts per endpoint per run, comparison with the previous window, and volume drop alerts, you are flying blind. The pipeline that ran successfully could have fetched zero new installments because the cursor got stuck.
The worst-case scenario isn't the pipeline that breaks and sends an alert. It's the pipeline that executes successfully and delivers incorrect data, so the cash flow report that finance opens on Monday morning is already calculated on top of a broken base.
What is possible once Sienge data reaches the warehouse
Cash flow and delinquency analysis with joined data
With accounts_receivable_receivable_bills and accounts_receivable_receivable_bill_installments in the warehouse, it is possible to calculate delinquency positions by development project, customer type, and due date with record-level precision—not as aggregated exports from the Sienge dashboard. By joining this with customers and enterprises, you can answer questions like: which projects concentrate the highest exposure of overdue receivables? Which customer types have the highest renegotiation rate?
Construction cost control on a cost-center and materials level
With bills, bills_budget_categories, bills_buildings_cost, and bills_departments_cost in the warehouse, you can build a view of budget commitment per project and per cost center at the entry level. Unlike Sienge's native reports, which are pre-aggregated by period, here you have the raw data to build any analysis dimension the controller needs.
Budget vs. actual comparisons for construction estimates
The endpoints building_cost_estimations_sheets, building_cost_estimations_resources, and building_cost_estimations_cost_estimate_resources bring in the analytic cost structure of the planned project. Alongside actual expenses in bills and daily construction logs in construction_daily_report, you can model cost variance per project phase and material group—a model that doesn't exist natively in any Sienge dashboard.
Portfolio analysis of sales contracts and receivables
With sales_contracts, units, enterprises, and price_tables in the warehouse, you can construct a portfolio sales view per project, highlighting contract stages, contracted values, indexation, and collection projections. Joining this with accounts_receivable_receivable_bill_installments closes the loop between signed contracts and actual cash collection positions.
Inventory management and material tracking
The endpoints inventory_movements, stock_reservations, and stock_inventories_items bring the historical ledger of inventory movements per project. With this in the warehouse, you can identify consumption per stage, variances against planned schedules, and cross-reference with quotation and purchase data from purchase_quotations_negotiations and purchase_requests_items.
Multi-company consolidation for accounting
With accountancy_entries, accountancy_accounts, accounts_balances, and companies in the warehouse, the controller managing multiple companies within the same group can consolidate the chart of accounts and balances into a single analytical model without needing to export reports from each company individually.
What is available in the connector
The Sienge connector delivers more than ninety endpoints ready to be materialized in the destination warehouse, covering the main platform modules:
Finance and Accounting
Endpoint | What it contains |
|---|---|
| Chart of accounts |
| Ledger entries |
| Automatic entries batches |
| Automatic entry logs |
| Batch entry items |
| Balances per account |
| Account statements |
| Accounting batches |
| Checking accounts |
| Accounting closures |
| Account balance (bulk) |
| Balance by account and cost center (bulk) |
| Bank movements (bulk) |
| Revenues (bulk) |
| Expenses (bulk) |
Accounts Receivable
Endpoint | What it contains |
|---|---|
| Invoices and bills receivable |
| Receivable installments |
| Budget categories of receivables |
| Receivables custodians |
| Customer debt balance (bulk) |
| Customer statement history (bulk) |
| Defaulters (bulk) |
| Defaulters by aging (bulk) |
Accounts Payable
Endpoint | What it contains |
|---|---|
| Accounts payable |
| Accounts payable by change date |
| Accounts payable installments |
| Taxes on accounts payable |
| Budget categories |
| Costs by department |
| Costs by project |
| Accounts payable attachments |
| Units linked to bills |
| Electronic invoices (NF-e) |
| NF-e payments |
| Linked NF-e |
Projects and Budgets
Endpoint | What it contains |
|---|---|
| Cost estimation spreadsheets |
| Estimate resources |
| Resource movement units |
| Cost estimate resources |
| Non-working days per project |
| Project progress logs |
| Daily construction log |
| Daily log event types |
| Daily construction log types |
| Estimate items (bulk) |
| Project resources (bulk) |
| Business budget (bulk) |
Sales Contracts and Units
Endpoint | What it contains |
|---|---|
| Sales contracts |
| Contract attachments |
| Contract guarantors |
| Real estate units |
| Unit features |
| Unit statuses |
| Real estate map |
| Property leasing |
| Property types |
| Sales (bulk) |
| Commissions |
| Commission settings by broker |
| Sales commissions |
| Price tables |
| Correction indices |
Inventory and Procurement
Endpoint | What it contains |
|---|---|
| Inventory ledger |
| Inventory reservations |
| Inventory item lists |
| Quote negotiations |
| Purchase request items |
| Quotations (bulk) |
| Supply contract measurements |
| Measurement items |
| Measurement attachments |
| Cost databases |
| Cost database resources |
| Cost database service items |
| Service item compositions |
Registries and Settings
Endpoint | What it contains |
|---|---|
| Companies |
| Projects/Enterprises |
| Customers |
| Customer attachments |
| Creditors |
| Creditor bank details |
| Creditor Pix details |
| Cost centers |
| Departments |
| Jobsites/sites |
| Cities |
| Marital status |
| Customer types |
| Payment terms types |
| Fixed assets |
| Movable assets |
| Professions |
| Resource groups |
| Trademarks |
| Units of measure |
| Service item groups |
| Invoice items (bulk) |
Supported destinations: BigQuery, Redshift, and PostgreSQL.
How to authenticate
Connector authentication requires three fields:
Subdomain: the Sienge account subdomain (the identifier in the API URLs, for example:
mycompany)User: the Sienge user's email address (for example:
your@email.com)Password: the Sienge user's password
Full documentation: docs.erathos.com/connectors/apis/sienge
Why outsource ingestion to Erathos
The conector premise is straightforward: maintaining ingestion pipelines shouldn't be the data team's responsibility. Pagination, rate limits, exponential backoff retries, schema evolution, failure reports, volume drop alerts, and backfills are all handled by the ingestion platform.
Once configured, the platform delivers:
End-to-end visibility of every run
Extraction time per endpoint, record counts per window, which windows were processed, and where retries occurred. When the construction cost report changes on the dashboard and the controller opens a ticket for the data team, there is a full tracing history to find the root cause.
Out-of-the-box alerting
Execution failures, volume drops per endpoint, and window delay flags are detected and routed via the alerting integrations your team already uses. No need to write that code.
Reprocessing as a platform operation
When you need to reprocess a window—either because the dbt model changed or a source correction arrived—it is handled as a simple platform operation, not an improvised sequence of DELETE + INSERT queries inside your warehouse.
Correct pagination, rate limit handling, schema evolution, and backfills are platform responsibilities. The data team focuses on modelling, not plumbing.
Available pipelines
Sienge to BigQuery: https://www.erathos.com/pipelines/sienge-bigquery
Sienge to Redshift: https://www.erathos.com/pipelines/sienge-redshift
Sienge to PostgreSQL: https://www.erathos.com/pipelines/sienge-postgresql
Sienge to Databricks: https://www.erathos.com/pipelines/sienge-databricks
Sienge to Azure SQL Server: https://www.erathos.com/pipelines/sienge-azure-sql-server
Sienge to Supabase: https://www.erathos.com/pipelines/sienge-supabase
Sienge to Amazon S3: https://www.erathos.com/pipelines/sienge-amazon-s3
Get started
Create your account on Erathos and connect Sienge to your warehouse in minutes. With your subdomain, username, and password, your first data loads will land without writing, maintaining, or monitoring a single line of pipeline code.
Daily construction, contract, financial, and inventory data shouldn't be locked inside an ERP, disconnected from the rest of your analytical model. Or worse, in a home-grown pipeline that will drain your team's attention month after month forever.
See the full connector documentation at docs.erathos.com/connectors/apis/sienge.