Best Query Engines for Amazon Redshift
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Compare the Top Query Engines that integrate with Amazon Redshift as of September 2025
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This a list of Query Engines that integrate with Amazon Redshift. Use the filters on the left to add additional filters for products that have integrations with Amazon Redshift. View the products that work with Amazon Redshift in the table below.
What are Query Engines for Amazon Redshift?
Query engines are software tools designed to retrieve and process data from databases or large datasets in response to user queries. They efficiently interpret and execute search requests, optimizing the retrieval process to deliver accurate and relevant results quickly. Query engines can handle structured, semi-structured, and unstructured data, making them versatile for various applications such as data analytics, business intelligence, and search engines. They often support complex query languages like SQL and can integrate with multiple data sources to provide comprehensive insights. By optimizing data retrieval, query engines enhance the performance and usability of data-driven applications and decision-making processes. Compare and read user reviews of the best Query Engines for Amazon Redshift currently available using the table below. This list is updated regularly.
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StarTree
StarTree
StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.Starting Price: Free -
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PuppyGraph
PuppyGraph
PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.Starting Price: Free -
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Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
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