Compare the Top Relational Database that integrates with Tableau as of September 2026

This a list of Relational Database that integrates with Tableau. Use the filters on the left to add additional filters for products that have integrations with Tableau. View the products that work with Tableau in the table below.

What is Relational Database for Tableau?

Relational database software provides users with the tools to capture, store, search, retrieve and manage information in data points related to one another. Compare and read user reviews of the best Relational Database for Tableau currently available using the table below. This list is updated regularly.

  • 1
    RaimaDB

    RaimaDB

    Raima

    RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree.
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  • 2
    SingleStore

    SingleStore

    SingleStore

    SingleStore (formerly MemSQL) is a distributed, highly-scalable SQL database that can run anywhere. We deliver maximum performance for transactional and analytical workloads with familiar relational models. SingleStore is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, geospatial, and full-text search formats. SingleStore delivers ultimate data ingestion performance at scale and supports built in batch loading and real time data pipelines. SingleStore lets you achieve ultra fast query response across both live and historical data using familiar ANSI SQL. Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real time.
    Starting Price: $0.69 per hour
  • 3
    Tiger Data

    Tiger Data

    Tiger Data

    Tiger Data is the creator of TimescaleDB, the world’s leading PostgreSQL-based time-series and analytics database. It provides a modern data platform purpose-built for developers, devices, and AI agents. Designed to extend PostgreSQL beyond traditional limits, Tiger Data offers built-in primitives for time-series data, search, materialization, and scale. With features like auto-partitioning, hybrid storage, and compression, it helps teams query billions of rows in milliseconds while cutting infrastructure costs. Tiger Cloud delivers these capabilities as a fully managed, elastic environment with enterprise-grade security and compliance. Trusted by innovators like Cloudflare, Toyota, Polymarket, and Hugging Face, Tiger Data powers real-time analytics, observability, and intelligent automation across industries.
    Starting Price: $30 per month
  • 4
    CrateDB

    CrateDB

    CrateDB

    The enterprise database for time series, documents, and vectors. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source distributed database running queries in milliseconds, whatever the complexity, volume and velocity of data.
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    HEAVY.AI

    HEAVY.AI

    HEAVY.AI

    HEAVY.AI is the pioneer in accelerated analytics. The HEAVY.AI platform is used in business and government to find insights in data beyond the limits of mainstream analytics tools. Harnessing the massive parallelism of modern CPU and GPU hardware, the platform is available in the cloud and on-premise. HEAVY.AI originated from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Expand beyond the limitations of traditional BI and GIS by leveraging the full power of modern GPU and CPU hardware so you can extract decision-quality information from your massive datasets without lag. Unify and explore your largest geospatial and time-series datasets to get the complete picture of the what, when, and where. Combine interactive visual analytics, hardware-accelerated SQL, and an advanced analytics & data science framework to find opportunity and risk hidden in your enterprise when you need to most.
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