How to Integrate Retool with Redfin

Navigate to redfin.com/news/data-center in your web browser. Redfin's Data Center provides free downloadable CSV files of residential real estate market statistics. Available datasets include national, metro, city, zip code, and neighborhood level data with metrics such as median sale price, median list price, homes sold, new listings, inventory, days on market, months of supply, median price per square foot, and average sale-to-list price ratio. Select the geographic granularity you need — for most internal tools, the Zip Code or City level files are most useful. Click the Download (.csv) link for each dataset you want. The files are updated weekly and cover multi-year historical data. To load this data into a database for querying in Retool, you have several options: Retool Database (the built-in managed PostgreSQL — navigate to Retool, find Retool Database in the left sidebar, and use the Import from CSV feature), a self-managed PostgreSQL instance (use pgAdmin or psql COPY command), or a cloud database like Supabase (use its Table Editor → Insert → Import from CSV). Create a table with column names matching the CSV headers: period_begin, period_end, region_type, region_name, city, state, state_code, property_type, median_sale_price, median_list_price, homes_sold, new_listings, inventory, days_on_market, median_sale_to_list, median_price_per_sqft. Import the CSV data into this table. Verify the import by running a SELECT COUNT(*) query to confirm row counts.

1-- SQL to create the Redfin market data table
2CREATE TABLE redfin_market_data (
3  id SERIAL PRIMARY KEY,
4  period_begin DATE,
5  period_end DATE,
6  region_type VARCHAR(50),
7  region_name VARCHAR(255),
8  city VARCHAR(255),
9  state_code VARCHAR(5),
10  property_type VARCHAR(100),
11  median_sale_price NUMERIC(12,2),
12  median_list_price NUMERIC(12,2),
13  homes_sold INTEGER,
14  new_listings INTEGER,
15  inventory INTEGER,
16  days_on_market NUMERIC(5,1),
17  median_sale_to_list NUMERIC(5,3),
18  median_price_per_sqft NUMERIC(8,2),
19  imported_at TIMESTAMP DEFAULT NOW()
20);
21
22-- Index for common query patterns
23CREATE INDEX idx_redfin_region ON redfin_market_data(region_name, state_code);
24CREATE INDEX idx_redfin_period ON redfin_market_data(period_begin);
25CREATE INDEX idx_redfin_region_period ON redfin_market_data(region_name, period_begin);

With the Redfin data in a database, connect Retool to it. In the Retool Resources tab, click Add Resource. Select PostgreSQL (or MySQL, depending on your database). If you used Retool Database, it is already available as a pre-configured Resource. For an external database, enter the host, port, database name, username, and password. Enable SSL if connecting to a cloud-hosted database. Click Save and test the connection. Once connected, create your first query in a Retool app. Open the Code panel, click Create new query, and select the database Resource. Write a SQL query to fetch market trend data for a selected region: use the Retool {{ }} syntax to reference a Select component value for the region name and a DateRangePicker for the date range. The query should retrieve monthly data points for the selected region across the full date range. In the app canvas, drag a Select component named regionSelect and populate its options from a separate query that retrieves all distinct region_name values from the database. Add a DateRangePicker for the date range. Add a Button labeled Load Data to trigger the main trend query. With results returned, bind a Chart component to the query data — set X axis to period_begin and add data series for median_sale_price, median_list_price, and median_price_per_sqft to create a comprehensive market trend chart.

1-- Main market trend query with dynamic region and date range
2SELECT
3  period_begin,
4  period_end,
5  region_name,
6  state_code,
7  property_type,
8  median_sale_price,
9  median_list_price,
10  homes_sold,
11  new_listings,
12  inventory,
13  days_on_market,
14  median_sale_to_list,
15  median_price_per_sqft
16FROM redfin_market_data
17WHERE
18  region_name = {{ regionSelect.value }}
19  AND property_type = {{ propertyTypeSelect.value || 'All Residential' }}
20  AND period_begin >= {{ dateRangePicker.startDate }}
21  AND period_begin <= {{ dateRangePicker.endDate }}
22ORDER BY period_begin ASC;

Redfin CSV data provides market trend context but not individual property lookups. For property-level queries (searching by address, retrieving sale history, current listing status), connect to a third-party API. ATTOM Data Solutions (attomdata.com) is the most comprehensive option: sign up at attomdata.com, navigate to the API section to obtain your API key, and review their property detail, sale history, and AVM (automated valuation model) endpoints. In Retool, create a REST API Resource: Base URL https://api.gateway.attomdata.com, and add an apikey header with your ATTOM API key value stored in a configuration variable. A basic ATTOM property lookup query: Method GET, Path /propertyapi/v1.0.0/property/detail, URL Parameters: address1 (street address), address2 (city + state). An alternative is the Zillow API on RapidAPI: subscribe to the Zillow API at rapidapi.com, create a REST API Resource with base URL https://zillow-com1.p.rapidapi.com, and add the X-RapidAPI-Key and X-RapidAPI-Host headers. Both APIs provide property details, sale history, and automated valuations that complement the Redfin market trend data already in your database. Wire a text input for address entry and a Search button to trigger the property lookup query, then display results in a detail Container alongside the market context from the database query.

1// JavaScript transformer for ATTOM property detail response
2const prop = data?.property?.[0] || {};
3const building = prop.building || {};
4const lot = prop.lot || {};
5const assessment = prop.assessment || {};
6const sale = prop.sale || {};
7
8return {
9  address: prop.address?.oneLine || 'N/A',
10  city: prop.address?.city || '',
11  state: prop.address?.state || '',
12  zip: prop.address?.postal1 || '',
13  county: prop.area?.countySecondaryName || '',
14  property_type: building?.summary?.propType || '',
15  year_built: building?.summary?.yearBuilt || 'N/A',
16  beds: building?.rooms?.beds || 'N/A',
17  baths: building?.rooms?.bathsTotal || 'N/A',
18  sqft: building?.size?.livingSize
19    ? Number(building.size.livingSize).toLocaleString()
20    : 'N/A',
21  lot_sqft: lot?.lotSize1
22    ? Number(lot.lotSize1).toLocaleString()
23    : 'N/A',
24  assessed_value: assessment?.assessed?.assdTtlValue
25    ? `$${Number(assessment.assessed.assdTtlValue).toLocaleString()}`
26    : 'N/A',
27  last_sale_price: sale?.salesHistory?.[0]?.amount?.saleAmt
28    ? `$${Number(sale.salesHistory[0].amount.saleAmt).toLocaleString()}`
29    : 'N/A',
30  last_sale_date: sale?.salesHistory?.[0]?.saleTransDate || 'N/A'
31};

Combine the Redfin CSV market data (from the database) with the property-level API data into a unified Retool dashboard. Structure the layout with two main sections. The top section is a Property Research panel: add a text input for address entry and a Search button that triggers the ATTOM or Zillow property lookup query. Display results in a Container on the right with all property details from the transformer. Below the property details, add a sale history Table bound to the historical sales data from the API response. The bottom section is a Market Context panel: this section is auto-populated based on the zip code returned from the property lookup. When the property lookup query succeeds, use an event handler to trigger the market trend query with the property's zip code pre-filled in the regionSelect. This creates an automatic flow where looking up a property immediately loads the relevant market context. Add a line Chart showing the 3-year median price trend for the zip code alongside a Stat component showing how the subject property's last sale price compared to the median at the time of sale. Add a Table showing recent comparable sales in the zip code from the ATTOM comparables endpoint (if available) or from the database filtered to the same zip code and similar property type and size range.

1-- Comparable sales query from Redfin CSV database
2-- Finds historical periods where the zip code had active market data
3SELECT
4  period_begin,
5  median_sale_price,
6  median_price_per_sqft,
7  homes_sold,
8  days_on_market,
9  inventory,
10  median_sale_to_list
11FROM redfin_market_data
12WHERE
13  region_name = {{ zipCodeFromLookup.value || propertyLookupQuery.data.zip }}
14  AND property_type = 'All Residential'
15  AND period_begin >= NOW() - INTERVAL '3 years'
16ORDER BY period_begin DESC
17LIMIT 36;

Redfin updates its publicly available CSV files weekly. To keep your Retool dashboard showing current data, set up a recurring refresh process. The simplest approach for small teams is a calendar reminder to manually download new CSVs weekly and re-import them to your database. For automated refresh, create a Retool Workflow with a weekly Schedule trigger. In the Workflow, use an HTTP Request block to download the latest Redfin CSV from the direct download URL (Redfin's CSVs have stable URLs that update with new data). Add a JavaScript block to parse the CSV content. Add a Resource Query block to upsert the new data into the database table using INSERT INTO ... ON CONFLICT (period_begin, region_name, property_type) DO UPDATE SET ... — this pattern inserts new rows and updates existing ones if the same period appears in both the old and new CSV. Add a Slack notification block to alert the team when the refresh completes or fails. Alternatively, if manual updates are acceptable, create a Retool app page with a simple CSV upload Form component that passes the file to a Python or JavaScript query for parsing and database insertion. For investment firms building production-grade Retool data platforms that combine Redfin CSV data, ATTOM API, and internal deal databases with automated refresh pipelines, RapidDev can help architect and build the full solution.

1-- Upsert query for automated Redfin CSV refresh
2-- Replace column values with actual CSV column mappings
3INSERT INTO redfin_market_data (
4  period_begin, period_end, region_name, state_code,
5  property_type, median_sale_price, median_list_price,
6  homes_sold, new_listings, inventory, days_on_market,
7  median_sale_to_list, median_price_per_sqft
8)
9VALUES
10  {{ newRowsFromCSV }}
11ON CONFLICT (period_begin, region_name, property_type)
12DO UPDATE SET
13  median_sale_price = EXCLUDED.median_sale_price,
14  median_list_price = EXCLUDED.median_list_price,
15  homes_sold = EXCLUDED.homes_sold,
16  new_listings = EXCLUDED.new_listings,
17  inventory = EXCLUDED.inventory,
18  days_on_market = EXCLUDED.days_on_market,
19  median_sale_to_list = EXCLUDED.median_sale_to_list,
20  median_price_per_sqft = EXCLUDED.median_price_per_sqft,
21  imported_at = NOW();