Connect Amazon Redshift to Querri
Bring your Redshift data into Querri and get AI-powered insights without writing SQL. Supports both Provisioned clusters and Serverless workgroups with PostgreSQL-compatible connectivity.
What You Can Analyze
Querri syncs your Redshift tables into its platform for fast, local analysis—no ongoing cluster load.
Provisioned & Serverless
Connect to both cluster-based and serverless Redshift deployments
Data Sync
Tables synced to Querri for fast local analysis without cluster load
Spectrum Support
Access Redshift Spectrum external tables querying S3 data
Multi-Schema
Query across multiple schemas in your Redshift database
PostgreSQL Compatible
Connects via PostgreSQL wire protocol for reliable connectivity
Schedule Syncs
Schedule data refreshes during off-peak hours to optimize costs
Analyze Warehouse Data in Plain English
Stop writing complex SQL queries to get answers from your Redshift warehouse. Querri syncs your tables locally and lets you ask questions in natural language—getting the same results without the syntax.
Ask things like 'Which product categories grew fastest last quarter?' or 'Show me customer retention by signup cohort' and get instant charts and tables.
Query synced Redshift data without writing SQL
Get instant visualizations from warehouse tables
Analyze data locally without cluster compute costs
Blend Redshift with Business Applications
Your Redshift warehouse captures transactional and operational data, but business context lives in CRMs, spreadsheets, and other tools. Querri lets you combine them all for a complete picture.
Join Redshift tables with HubSpot contacts, Google Sheets budgets, or any other connected source—no data engineering pipelines required.
Combine Redshift tables with CRM and spreadsheet data
Cross-reference warehouse data with live business sources
Unified analysis without building data pipelines
How the Integration Works
Authentication
Username/password via PostgreSQL wire protocol; SSL required by default.
Security
SSL enforced; Querri IP 18.189.33.77 for VPC security group whitelisting.
Sync Method
Data copied to Querri for local analysis—no ongoing cluster query load.
Read-Only Access
Querri only reads data; dedicated SELECT-only user recommended.
Explore More Integrations
Connect all your data sources to Querri for a complete picture.
Frequently Asked Questions
Common questions about connecting Amazon Redshift to Querri.
Querri is an AI-powered Redshift analytics tool that lets business users query their data warehouse using natural language. It syncs your Redshift tables locally for fast analysis without putting ongoing load on your cluster, and translates plain-English questions into results.
Yes. Querri translates your natural language questions into optimized queries automatically. Ask something like 'Which product categories grew fastest last quarter?' and Querri generates the query, runs it against your synced data, and returns interactive charts and tables.
Go to Settings in Querri and click Add Connector. Enter your Redshift cluster endpoint, port (default 5439), database name, and read-only credentials. Whitelist Querri's IP address 18.189.33.77 in your VPC security group, and test the connection.
Yes. Unlike Querri's PostgreSQL and MySQL integrations which query live, the Redshift integration syncs table data into Querri's own storage. This means your Redshift cluster is not under continuous load from Querri queries, and you can schedule syncs during off-peak hours.
Querri is SOC 2 Type II certified and uses AES-256 encryption for data at rest and in transit. SSL is required by default for Redshift connections. We recommend creating a dedicated read-only user with SELECT-only permissions and whitelisting IP 18.189.33.77.
Yes. Querri supports both Provisioned Redshift clusters and Redshift Serverless workgroups. The connection setup is the same for both—provide your endpoint, database, and credentials. RA3 node types are also fully supported.
Redshift uses port 5439 by default, which is different from standard PostgreSQL's port 5432. Querri connects via the PostgreSQL wire protocol but uses Redshift's default port. Make sure port 5439 is open in your VPC security group for Querri's IP.
Yes. Querri provides drag-and-drop dashboards with 8 chart types powered by Plotly. Pin any query result to a dashboard, schedule data syncs and automatic refreshes, and embed dashboards into your applications using the Embed SDK.
Yes. Querri can access Redshift Spectrum external tables that query data stored in Amazon S3. This lets you analyze both your Redshift warehouse data and your S3 data lake through the same natural language interface.
You can schedule data syncs at whatever frequency you need using Querri's cron scheduling feature. Many users schedule syncs during off-peak hours to minimize cluster load and costs. You can also trigger manual syncs at any time.
Yes. Querri lets you blend synced Redshift tables with data from Google Sheets, Salesforce, HubSpot, CSV files, and other connected databases. You can join warehouse data with live business data without building ETL pipelines.
Querri is designed for non-technical users who need to report on Redshift data without learning SQL. Users ask questions in plain English, get instant charts and tables, and can build automated reports and dashboards without any coding.
Only during data syncs. Querri copies your selected tables during scheduled sync windows, and after that all analysis happens locally on Querri's platform. Your cluster is not queried during day-to-day use, keeping performance impact minimal.
Yes. Querri generates interactive Plotly visualizations from your synced Redshift data, including bar charts, line charts, scatter plots, pie charts, and more. Every query result can be visualized with a single click and pinned to a drag-and-drop dashboard.
Run CREATE USER querri_reader PASSWORD 'your_password'; then GRANT SELECT ON ALL TABLES IN SCHEMA public TO querri_reader;. Since Redshift uses the PostgreSQL wire protocol, user management follows familiar PostgreSQL syntax. We recommend a SELECT-only user for maximum safety.