What are the best alternatives to Postgres for analytics?

For analytics with Metabase, several alternatives to PostgreSQL offer enhanced performance and specialized features, primarily focusing on columnar storage and data warehousing. These options are designed to handle large datasets and complex analytical queries more efficiently than traditional row-oriented databases like PostgreSQL. The best alternatives for analytics that are supported by Metabase include: **Cloud Data Warehouses & Analytical Databases:** * **Amazon Redshift** A fully-managed, petabyte-scale data warehouse service from Amazon Web Services, known for querying large datasets and integrating with other AWS services. * **Google Cloud BigQuery** A serverless and highly scalable data warehouse that allows for managing and analyzing extensive datasets without infrastructure management. * **Snowflake** A unified AI Data Cloud platform that provides seamless access to diverse datasets at massive scale and offers an elastic compute engine for various workloads. * **ClickHouse** An open-source, column-oriented database management system built for high-performance analytical queries. * **Druid** An open-source, distributed data store that combines features of data warehouses, time-series databases, and search technologies, optimized for real-time analytics. * **Vertica (OpenText Analytics Database)** An analytics platform designed for fast, real-time data processing and advanced machine learning. * **Databricks** A unified analytics platform built on Apache Spark, supporting various analytical workloads. * **Teradata VantageCloud** A cloud-native data warehouse platform for enterprise-scale analytics, integrating structured and semi-structured data across cloud and hybrid environments. * **Amazon Athena** A fully managed service for querying data directly in Amazon S3 using standard SQL. **Query Engines (often used with data lakes or other data sources):** * **SparkSQL** An Apache Spark module for SQL processing that can query various data sources. * **Presto** An open-source distributed SQL query engine designed for running analytical queries against various data sources, including data lakes. These alternatives excel in analytical tasks due to their architecture, which often includes columnar storage, data compression, parallel processing, and optimized query engines, making them ideal for business intelligence, data warehousing, and real-time reporting.

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These options are designed to handle large datasets and complex analytical queries more efficiently than traditional row-oriented databases like PostgreSQL.\n\nThe best alternatives for analytics that are supported by Metabase include:\n\n**Cloud Data Warehouses \u0026 Analytical Databases:**\n* **Amazon Redshift** A fully-managed, petabyte-scale data warehouse service from Amazon Web Services, known for querying large datasets and integrating with other AWS services.\n* **Google Cloud BigQuery** A serverless and highly scalable data warehouse that allows for managing and analyzing extensive datasets without infrastructure management.\n* **Snowflake** A unified AI Data Cloud platform that provides seamless access to diverse datasets at massive scale and offers an elastic compute engine for various workloads.\n* **ClickHouse** An open-source, column-oriented database management system built for high-performance analytical queries.\n* **Druid** An open-source, distributed data store that 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{ "input": { "contents": "You are answering a user query. Be concise but helpful.\nIf you mention products or brands, be specific.\nDo not invent facts. If unsure, say you are unsure.\n\nBrand under analysis: Metabase\nBrand website: https://metabase.com\nEntity focus: customer = Metabase\n\nUser query: What are the best alternatives to Postgres for analytics?", "model": "gemini-2.5-flash" }, "model": "gemini-2.5-flash", "provider": "gemini" }

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