From Bitrix24 CRM to Amazon S3: managed, scheduled, no code.
Kondado automatically replicates Bitrix24 CRM data to Amazon S3, including Deals, Contacts, Companies, and 17 other pipelines, updating your data lake every 5 minutes, 15 minutes, hourly, or daily based on your configuration.
Kondado enables you to replicate data from Bitrix24 CRM to Amazon S3 on a configurable schedule, eliminating manual exports and keeping your data lake current with minimal effort. Simply connect your Bitrix24 CRM account as a data source, configure Amazon S3 as your destination, and select which pipelines to replicate from the available options. The platform handles the extraction and loading automatically, delivering structured data files to your S3 bucket ready for immediate analysis or further processing.
Once your Bitrix24 CRM data lands in Amazon S3, you can query it directly with Amazon Athena, process it with Presto or Dremio, or load it into BigQuery and PostgreSQL for deeper analysis. This setup supports advanced sales analytics, custom reporting, and data virtualization without requiring your team to maintain complex API connections or manual data transfers.
With the Deals, Contacts, and Companies pipelines replicated to Amazon S3, you can build comprehensive sales funnel analytics and customer segmentation models using Athena or Presto to identify conversion bottlenecks. Join this Bitrix24 CRM data with information from BigQuery or PostgreSQL to create unified views of account health and engagement patterns across your entire customer base. Agency analysts can then feed these combined datasets into custom dashboards built in Power BI or Looker Studio to track team productivity and sales performance without maintaining complex API connections.
Try out all the features for free for 14 days
Replicated to Amazon S3
Bitrix24 CRM data available for Amazon S3
Tables Kondado writes into your Amazon S3, on a schedule you control.
20
available pipelines
450
extractable fields
Amazon S3
Destination
Available integrations
Actitivity
Catalogs
Presents information such as Catalog ID, name, and origin IDs, facilitating data organization.
Companies
Contains fields such as Company ID, address, company type, and annual revenue, essential for client management.
Companies: custom fields (data)
Includes custom fields such as Company ID and additional data, allowing for the customization of information.
Contacts
Features fields such as Contact ID, address, created timestamp, and comments, fundamental for relationship management.
Contacts: companies
Links contacts with companies through fields such as Contact ID and Company ID, facilitating data integration.
Contacts: custom fields (data)
Includes custom fields such as Contact ID and additional data, allowing for the adaptation of information.
Deals
Contains information such as Deal ID, value, status, and created timestamp, essential for sales tracking.
Deals: custom fields (data)
Includes custom fields such as Deal ID and additional data, allowing for the customization of sales information.
Deals: custom fields (meta)
Presents metadata of custom fields such as Deal ID and additional information, facilitating sales analysis.
Deals: pipelines
Includes information on pipeline ID, name, and status, allowing for analysis of the business flow.
Deals: pipeline stages
Presents details on stage ID, name, and order, facilitating the tracking of sales progress.
Deals: products
Contains information on product ID, name, and price, allowing for analysis of the product portfolio in deals.
Deals: quotes
Provides data on quote ID, total value, and status, essential for managing commercial proposals.
Deals: quote products
Includes information on product ID, quantity, and unit price, detailing the items included in quotes.
Deals: stage history
Records stage changes, including deal ID, date, and new stage, allowing for analysis of progress.
Leads
Contains information on lead ID, name, status, and creation date, essential for lead management.
Leads: custom fields (data)
Includes custom data associated with the lead, such as ID and specific values, allowing for more precise segmentation.
Leads: products
Provides information on products associated with the lead, including product ID and quantity, facilitating interest analysis.
Products
Includes details on product ID, name, price, and description, essential for managing the product catalog.
Sync data automatically — no code, no manual exports.
1
Connect Bitrix24 CRM to Kondado
Authenticate your Bitrix24 CRM account by providing your portal URL and API credentials in the Kondado interface. Select the specific pipelines you want to replicate, such as Deals, Contacts, or Activity data.
2
Configure Amazon S3 Destination
Enter your AWS access keys and specify the target S3 bucket and folder path where Bitrix24 CRM data should land. Kondado supports standard S3 configurations that work seamlessly with Athena, Presto, and other analytics engines.
3
Schedule and Activate Replication
Choose your update frequency from options including every 5 minutes, 15 minutes, hourly, or daily based on your business needs. Activate the pipeline to begin automated replication, then monitor the data flow from Bitrix24 CRM directly into your Amazon S3 data lake.
Try out all the features for free for 14 days
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Answers about sending Bitrix24 CRM data to Amazon S3 automatically
How does Kondado replicate Bitrix24 CRM data to Amazon S3?▼
Kondado connects to your Bitrix24 CRM account via API and extracts data from your selected pipelines on a configurable schedule. The platform automatically loads this data into your Amazon S3 bucket as structured files, maintaining data types and relationships without requiring manual exports or coding. You can monitor replication status and pipeline health directly from the Kondado interface.
What Bitrix24 CRM data can I send to Amazon S3?▼
Kondado offers 20 distinct pipelines covering Deals, Contacts, Companies, Leads, Products, Activity, and related metadata including custom fields and stage history. Each pipeline contains specific entities like deal values, contact details, company revenue data, and pipeline stage transitions, totaling over 450 available fields for analysis in your data lake.
How often does Kondado update my Bitrix24 data in Amazon S3?▼
You can configure replication to run every 5 minutes, 15 minutes, hourly, or daily depending on your analytics requirements and API rate limits. This near-real-time schedule ensures your Amazon S3 data lake stays current without overwhelming your Bitrix24 CRM instance with excessive API calls.
What file format does Bitrix24 data arrive in when sent to Amazon S3?▼
Data arrives in your S3 bucket as compressed JSON or Parquet files, optimized for querying with Amazon Athena, Presto, and Dremio. The structured format preserves nested relationships from Bitrix24 CRM entities, making it easy to load into BigQuery or PostgreSQL for further transformation.
Can I combine Bitrix24 CRM data with other sources in Amazon S3?▼
Yes, Amazon S3 serves as a central data lake where Bitrix24 CRM data can coexist with information from Google Sheets, advertising platforms, and databases. You can join these datasets using Athena or load everything into Power BI and Looker Studio to create comprehensive reports that span sales, marketing, and finance.
Does Kondado capture custom fields from Bitrix24 CRM in Amazon S3?▼
Yes, dedicated pipelines for Deals, Contacts, Companies, and Leads specifically handle custom fields data and metadata, ensuring your unique CRM configurations transfer to Amazon S3. This includes both the values stored in custom fields and their structural definitions, preserving your tailored Bitrix24 setup for accurate reporting.
How does Kondado handle schema changes in Bitrix24 CRM?▼
When you add new custom fields or modify existing ones in Bitrix24 CRM, Kondado automatically detects these schema changes in subsequent replication cycles. The platform updates the corresponding files in Amazon S3 to include new columns while maintaining historical data integrity, ensuring your analytics pipelines continue running without manual intervention.
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