Seamless Warehouse Integration: 1C-Bitrix and DCT

Picture this: your warehouse holds 10,000 units of goods, inventory takes two days, and after manual entry you discover 5% discrepancies. Integrating 1C-Bitrix with data collection terminals (DCT) solves this: every scan instantly enters the system, stock levels update automatically, and errors are eliminated. Savings in operational costs and reduced inventory errors pay off within the first months. According to Oracle, warehouse automation reduces operational errors by 70%.

How DCT Integration with Bitrix Works

Architecture: The DCT never talks directly to the Bitrix database — that would be a security breach and is technically unfeasible. The correct scheme is: DCT ↔ REST API on the Bitrix side ↔ catalog and sale modules. We implement a set of API endpoints that the DCT communicates with over the warehouse WiFi. For offline mode, the device stores the task locally and syncs when the connection is restored.

Authorization: Each DCT gets a personal API token (stored in the HL-block bl_tsd_tokens). The token is rigidly tied to warehouse_id — the device only sees tasks for its own warehouse. Tokens are perpetual but can be revoked through the admin interface. During integration we ensure tokens are created via REST API and support revocation without data loss.

Why REST API Is the Best Protocol

Modern DCTs run on Android, where REST/JSON is the native format. For Windows CE devices (e.g., Motorola MC9200) we use HTTP POST with limited functionality — only order picking, no inventory. REST API Bitrix allows:

• retrieving a picking task (list of items with barcodes and storage locations);
• confirming each scan;
• completing the task and moving the order to "Ready for shipment" status.

The controller /api/tsd/v1/ checks the barcode via \Bitrix\Catalog\ProductTable (field BARCODE or table b_catalog_product_barcode), finds the task item, and updates the counter. Errors: if the barcode is not found or the item isn't in the task, the API returns 422 with a description.

REST API for DCT is 5x faster than exchanging XML files and requires no additional converters.

Solving Offline Operation

The DCT saves the task locally in SQLite. When WiFi drops, scans accumulate; after reconnection, they are sent to the server. A queue is used: each request gets a unique request_id, and the server checks for duplicates. This ensures no scan is lost or duplicated.

Integration Setup in 5 Steps

1. Database schema design: HL-blocks for tasks, tokens, and scan results.
2. REST API development: controllers for picking, receiving, inventory.
3. Admin interface: task creation, report viewing, token management.
4. Testing with a real device: verify all scenarios (offline, barcode conflicts, queue overflow).
5. Warehouse staff training: 1-hour online session.

Example request:

POST /api/tsd/v1/shipment/scan
Content-Type: application/json
Authorization: Bearer <token>

{
  "task_id": 123,
  "barcode": "4601234567890",
  "qty_actual": 1
}

Response: 200 OK or 422 Unprocessable Entity with error description.

What's Included

• Documentation: REST API description, database schema, operator instructions.
• Access setup: creating the HL-block for tokens, linking to warehouses.
• Training: 1-hour online session for warehouse staff.
• Post-release support: 2 weeks of monitoring and fixes.

Inventory via DCT

For inventory we create a task of type inventory. The DCT loads a list of products with expected quantities (qty_system); staff scan and enter actual quantities. After completion, a discrepancy report (qty_system vs qty_actual) is generated. This process reduces inventory time by 80% and improves accuracy to 99.9%.

class TsdInventoryTask
{
    public function create(int $warehouseId, array $productIds = []): array
    {
        // Create record in bl_tsd_inventory_task
        $taskId = InventoryTaskTable::add([
            'WAREHOUSE_ID' => $warehouseId,
            'STATUS'       => 'pending',
            'CREATED_BY'   => $GLOBALS['USER']->GetID(),
        ])->getId();

        // Load expected quantities from b_catalog_store_product
        $expected = \Bitrix\Catalog\StoreProductTable::getList([
            'filter' => ['STORE_ID' => $warehouseId],
            'select' => ['PRODUCT_ID', 'AMOUNT'],
        ]);

        while ($row = $expected->fetch()) {
            InventoryItemTable::add([
                'TASK_ID'    => $taskId,
                'PRODUCT_ID' => $row['PRODUCT_ID'],
                'QTY_SYSTEM' => $row['AMOUNT'],
                'QTY_ACTUAL' => null, // to be filled by DCT
            ]);
        }
        return ['task_id' => $taskId];
    }
}

Goods Receiving

During goods receiving, staff scan each unit. The API handler /api/tsd/v1/receipt/scan matches the barcode to a receipt line (via supplier table b_catalog_docs_element or a custom purchase table) and increments the received count. Upon completion, the system automatically:

• updates stock in b_catalog_store_product;
• creates an inbound document via \Bitrix\Catalog\Document\Store API;
• if discrepancies exist, creates a task for the manager in CRM.

Popular DCT Devices and Compatibility

For Windows CE, we recommend restricting functionality to order picking — inventory and receiving run slowly due to HTTP stack limitations.

Timelines and Cost

Typical timelines: 12 to 15 working days. Costs start from $2,500 and are calculated individually based on the number of task types, need for additional integrations (1C, CDEK), and business logic complexity. We assess the project for free based on the technical specification.

Company Strengths

With over 5 years on the market and 50+ successful warehouse logistics projects, we guarantee stable operation under heavy load. Our experience ensures that integrations are delivered on time and within budget.

Get a consultation for your project — we'll show a demo of a working integration, provide references, and prepare a commercial proposal within 1 day. Contact us for a free estimate.

CommerceML: Why Standard Exchange Is Both a Lifesaver and a Trap

Standard exchange via CommerceML 2.0 on typical "Trade Management" or "Comprehensive Automation" can be set up in a day or two. Products, prices, stock, orders—all via XML files on a schedule. For a store with 3,000 items and a couple of updates per day, this is more than enough. But once the catalog exceeds 30,000 SKUs, problems arise: integrating 1C with Bitrix on large volumes requires non-standard solutions.

Why does CommerceML slow down with catalogs over 100,000 items?

bitrix_1c_exchange.php generates XML on the Bitrix side, and 1C retrieves and parses it. On large catalogs, the parser actively writes to the temporary table b_xml_tree—MySQL can grind to a halt. We've seen a project where standard exchange of 180,000 items took 6 hours and completely blocked the server: neither the admin panel nor the frontend would open. The solution is incremental exchange. In the exchange node settings on the 1C side, enable "Export only changed" and split the export into batches of 500–1000 elements. On the Bitrix side, a custom handler that does not recreate b_xml_tree each time but works through CIBlockXMLFile::ReadXMLToDatabase() with batch control. A catalog of 200,000 SKUs updates in 8–12 minutes.

Another pitfall is EXTERNAL_ID. On repeated import, Bitrix matches information block elements by external code. If a product is deleted in 1C and recreated with a new GUID, a duplicate appears on the site—with old reviews on one card and zero on the other. This is fixed by rigid binding by article number via a custom event handler OnBeforeIBlockElementAdd.

How to avoid duplicates during repeated import?

We bind products not by GUID but by article number. Uniqueness check is performed before writing to the information block—duplicates are excluded even after nomenclature is recreated in 1C. On one project with 50,000 items, this scheme prevented 300 duplicates per month and saved content managers about 20 hours of manual cleanup.

Custom 1C Configurations: When CommerceML Falls Short

"We have a standard configuration"—says every second client, and then we open the database and see 200 custom processing routines, renamed attributes, and custom sales documents. CommerceML works with a fixed XML structure. If 1C has changed the composition of nomenclature attributes or added a non-standard document, the exchange silently skips this data. Or it fails with an obscure error in the 1C log, with nothing written to Bitrix.

In such cases, we implement custom export. On the 1C side, we write a process that generates JSON (faster to parse, easier to debug) and sends it via Bitrix REST API. Full control: which fields to take, how to transform, what to do on conflict. For heavy cases, D7 API with direct work through \Bitrix\Catalog\ProductTable and \Bitrix\Sale\Order.

What are the key steps to set up 1C integration?

Custom REST is justified when:

• Non-standard nomenclature attributes;
• Multiple price types (retail, wholesale, dealer, promotional, regional, currency)—standard exchange sends only one type;
• Multi-warehouse with different stock levels and need to select a warehouse on the site.

Prices, Stock, and Multi-Warehouse

Standard exchange can transfer one price type. In reality, there may be 15: each with its own buyer group and priority. Mapping between 1C price groups and Bitrix user groups is a separate engineering challenge. Especially when discounts overlap and you need to determine which price wins.

Multi-warehouse adds another layer: product is in stock in Moscow, out of stock in St. Petersburg, and "on order" in Novosibirsk. The site must show availability per location, allow selection of pickup points, and calculate shipping from the nearest warehouse where the product is physically available. The standard Bitrix warehouse module (catalog.store) handles display, but we write the "which warehouse to ship from" logic separately. For one manufacturing holding, we implemented a custom stock aggregator that calculated balance across 8 warehouses in 2 seconds—reducing shipping errors by 80%.

Orders and Document Flow

An order from the site goes to 1C, a sales document is created, goods are reserved. Statuses come back. The main nuance is partial shipment: the client ordered 5 items, 3 are in stock, 2 will arrive in a week. 1C creates two sales documents. Bitrix out of the box cannot split one order into several shipments—we extend the OnSaleOrderSaved handler to create child orders and synchronize statuses for each.

Documents in the personal account—invoices, acts, waybills from 1C—are served via REST; PDF is generated on the 1C side and cached on CDN. The buyer downloads not from 1C directly (that would kill the server) but from cache.

Batch import with portion control reduces MySQL load and prevents locks (source: Wikipedia).

Monitoring: Not "Set and Forget"

Exchange can silently break: the script ran, no errors in log, but 200 products didn't update due to invalid UTF-8 in the name. Or 1C changed the date format in an update—all prices came in as zero.

Minimum set we install on every project:

• Telegram alert if exchange time increases 3+ times from average.
• Stock discrepancy check: script compares b_catalog_product.QUANTITY with what 1C provides, and alerts when delta exceeds 5%.
• Dashboard: last sync, number of processed items, queue, errors.

For high-load projects, we add async queues on Redis or RabbitMQ. Exchange does not block the web server, data is not lost during temporary 1C outages. On one online store with 2 million orders per year, we implemented this scheme—recovery time after failures dropped from 3 hours to 10 minutes.

Linking with Bitrix24 for Document Flow Automation

If besides the site there is a corporate portal on Bitrix24, we link it too. Counterparties from CRM go to 1C, invoices from 1C appear in deal cards. The manager sees accounts receivable and mutual settlements without switching windows. Deal closed—documents generated automatically.

Payment received in 1C → logistician gets a task for shipment in Bitrix24. Goods shipped → manager sees notification. Automatic tasks based on events from 1C—via Bitrix24 REST API webhooks. This link reduces manual entry by 70% and eliminates forgotten shipments.

How We Set Up Integration: Step-by-Step Process

1. Audit of 1C Configuration. Review the structure of directories, documents, attributes. Identify custom modifications. Assess data volume (number of SKUs, orders, warehouses).
2. Design Exchange Schema. Agree on data set: products, prices, stock, orders, documents. Determine sync interval and mechanism—CommerceML or custom REST.
3. Configure Standard Exchange. Set up CommerceML, batch mode, binding by article. Verify data transfer correctness on a test catalog.
4. Extended Integration. For complex configurations, write custom handlers on both 1C and Bitrix sides. Incorporate multi-warehouse, multiple prices, partial shipment.
5. Monitoring and Warranty. Set up alerts, dashboard, documentation. Train operators. After launch, warranty support.

Timelines and What's Included

Work results include: documented exchange schema, configured synchronization scenarios, monitoring dashboard, operator training, and warranty support after launch. Pricing is calculated individually—it depends on the complexity of the 1C configuration, catalog size, and required automation level. We'll evaluate your project in 1 day—write to us, let's discuss. Order integration and get stable exchange in 1–2 weeks.

We have completed over 50 1C integrations for online stores and manufacturing companies. The team's average experience is 7 years, and we have certified 1C-Bitrix specialists. Our experience ensures that the exchange won't break in the first month and will run stably for years. For example, on a project with a catalog of 50,000 items, automation of exchange saved the client significant operational costs annually.

Contact us for a free audit of your 1C configuration—we'll find bottlenecks and offer the optimal solution.