How does Kondado replicate Tray data to Redshift without coding?

Kondado provides a direct connection to Tray's API and automatically maps your eCommerce data to Redshift-compatible schemas. You authenticate your Tray account through the interface, select your desired pipelines, and configure the destination warehouse without writing SQL or Python scripts. The platform manages schema creation, data type conversion, and incremental updates on your chosen schedule.

What Tray eCommerce data can I replicate to my Redshift warehouse?

You can replicate 14 distinct pipelines including Orders, Customers, Payments, Products, Discount Coupons, and Order Invoices with a total of 328 available fields. This covers transaction details, customer profiles, product catalogs, newsletter subscriptions, and financial records including Mercado Livre specific order information. Each pipeline can be selected individually to customize exactly which data entities populate your warehouse.

How often does Tray data update in Redshift?

Kondado updates your Redshift warehouse on a configurable schedule that you control, with options ranging from every 5 minutes to daily intervals depending on your analytical needs. Near-real-time updates every 5 or 15 minutes support operational dashboards, while hourly or daily schedules optimize compute costs for batch reporting. You can adjust these frequencies per pipeline to balance freshness with resource efficiency.

Can I combine Tray data with other sources in Redshift?

Yes, Redshift serves as a central repository where Tray eCommerce data can coexist with information from additional Kondado sources and external systems. You can join customer records from Tray with marketing data loaded via Google Sheets or financial information from BigQuery to create comprehensive business views. This unified approach enables cross-functional analysis that connects sales transactions with advertising spend and inventory management across multiple platforms.

What data structure does Tray data use in Redshift tables?

Kondado creates structured tables in Redshift that mirror your selected Tray pipelines, with each entity type such as Orders, Customers, or Products residing in its own optimized table. The schema preserves field names and data types from Tray while converting them to Redshift-compatible formats for efficient querying. Relationships between entities maintain referential integrity to support complex analytical joins across your eCommerce data.

Does Kondado support Tray's Mercado Livre order details in Redshift?

Yes, Kondado includes a dedicated Order Details: Mercado Livre pipeline that captures marketplace-specific data including customer IDs, estimated delivery dates, and product information unique to Mercado Livre transactions. This pipeline replicates alongside standard Order Details to provide comprehensive coverage for businesses selling across multiple channels. You can analyze marketplace performance separately or consolidate it with direct sales data for unified revenue reporting.

How do I analyze Tray sales data once it is in Redshift?

With your Tray data stored in Redshift, you can run complex SQL queries to calculate metrics like customer lifetime value, average order value, and sales velocity across different time periods. Connect Power BI , Looker Studio , or PostgreSQL -compatible tools to visualize trends and build custom dashboards that refresh automatically. The columnar storage format of Redshift enables fast aggregation of large transaction volumes for deep business intelligence.

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Send Tray Data to Redshift Automatically

Kondado enables automated pipelines between Tray and Amazon Redshift, allowing you to replicate your eCommerce data without writing code or managing complex API connections. Simply authenticate your Tray account as a data source and designate Redshift as your destination to establish the automated flow. The platform handles the entire extraction and loading process on a configurable schedule, ensuring your data warehouse stays current with your latest transactions, customer information, and product catalogs.

Kondado replicates data from Tray to Redshift on a configurable schedule, offering 14 pipelines including Orders, Customers, Payments, and Products with 328 total fields, enabling automated data warehouse updates without manual extraction or coding.

Once configured, your Tray data flows directly into Redshift structures optimized for high-performance analytical queries. You can run complex SQL analyses on sales performance, track inventory movements across channels, and monitor customer behavior patterns. Connect your favorite business intelligence tools like Power BI or Looker Studio to create comprehensive dashboards that update automatically as fresh data arrives from your eCommerce operations.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Replicate your Orders pipeline to analyze transaction trends, fulfillment efficiency, and delivery performance directly within Redshift, enabling you to identify high-value customers and optimize shipping strategies based on historical data. The Customers pipeline delivers comprehensive contact information and behavioral data that powers sophisticated segmentation analysis and customer lifetime value calculations across your marketing campaigns. Combine these with the Payments pipeline to reconcile financial transactions, track revenue recognition patterns, and build unified financial reports that connect sales activity with cash flow analysis while supporting compliance requirements.

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Tray data available for Redshift

available pipelines

328

extractable fields

Available integrations

Integration	Description
Customers	Includes information such as name, email, and registration date, along with modification date and last visit.
Discount Coupons	Contains details such as coupon code, creation date, and discount value, along with usage restrictions.
Newsletters	Presents information about the customer's email, newsletter status, and creation and modification dates.
Payments	Includes data on payment methods, status, and values of transactions made by customers.
Orders	Provides information such as order ID, order date, and delivery status, along with customer details.
Order Details	Includes detailed information such as order ID, billing address, and additional cart values.
Order Details: Mercado Livre	Presents data such as customer ID, estimated delivery date, and information about the purchased product.
Additional Product Information for Orders	Contains additional information such as product ID and product name related to each order.
Order Invoices	Includes data such as invoice ID and product CFOP, essential for accounting.
Order Transactions	Provides information on transaction status and values associated with each order made.
Products	Table contains information about products, including id, name, and variants. Fields such as attributes_id and attributes_value provide additional details.
Products (Kits)	Table presents product kits, detailing id and attributes. Fields such as attributes_customer_attribute_id provide information about the characteristics of the kits.
Sold Products	Table displays sold products, including id and sales information. Fields such as order_id and order_item_quantity help understand sales performance.
Products: Variants	Table details product variants, including id and attributes. Fields such as additionalproductinfo_product_id and additionalproductinfo_variant_id provide specific information about each variant.

Customers

Includes information such as name, email, and registration date, along with modification date and last visit.

Discount Coupons

Contains details such as coupon code, creation date, and discount value, along with usage restrictions.

Newsletters

Presents information about the customer's email, newsletter status, and creation and modification dates.

Payments

Includes data on payment methods, status, and values of transactions made by customers.

Orders

Provides information such as order ID, order date, and delivery status, along with customer details.

Order Details

Includes detailed information such as order ID, billing address, and additional cart values.

Order Details: Mercado Livre

Presents data such as customer ID, estimated delivery date, and information about the purchased product.

Additional Product Information for Orders

Contains additional information such as product ID and product name related to each order.

Order Invoices

Includes data such as invoice ID and product CFOP, essential for accounting.

Order Transactions

Provides information on transaction status and values associated with each order made.

Products

Table contains information about products, including id, name, and variants. Fields such as attributes_id and attributes_value provide additional details.

Products (Kits)

Table presents product kits, detailing id and attributes. Fields such as attributes_customer_attribute_id provide information about the characteristics of the kits.

Sold Products

Table displays sold products, including id and sales information. Fields such as order_id and order_item_quantity help understand sales performance.

Products: Variants

Table details product variants, including id and attributes. Fields such as additionalproductinfo_product_id and additionalproductinfo_variant_id provide specific information about each variant.

See all available data →

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How to send Tray data to Redshift

Sync data automatically — no code, no manual exports.

Connect Your Tray Account

Authenticate your Tray credentials in Kondado to establish the data source connection, enabling access to your eCommerce transactions and customer records.

Configure Redshift Settings

Enter your Amazon Redshift cluster endpoint, database credentials, and schema preferences to designate where your Tray pipelines should land.

Select Pipelines and Schedule

Choose specific pipelines like Orders, Customers, or Payments from the 14 available options, then configure your update frequency to automate data replication.

Try out all the features for free for 14 days