Best Data Warehouse Software for Metabase
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Compare the Top Data Warehouse Software that integrates with Metabase as of April 2026
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This a list of Data Warehouse software that integrates with Metabase. Use the filters on the left to add additional filters for products that have integrations with Metabase. View the products that work with Metabase in the table below.
What is Data Warehouse Software for Metabase?
Data warehouse software helps organizations store, manage, and analyze large volumes of data from different sources in a centralized, structured repository. These systems support the extraction, transformation, and loading (ETL) of data from multiple databases and applications into the warehouse, ensuring that the data is cleaned, formatted, and organized for business intelligence and analytics purposes. Data warehouse software typically includes features such as data integration, querying, reporting, and advanced analytics to help businesses derive insights from historical data. It is commonly used for decision-making, forecasting, and performance tracking, making it essential for industries like finance, healthcare, retail, and manufacturing. Compare and read user reviews of the best Data Warehouse software for Metabase currently available using the table below. This list is updated regularly.
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1
Teradata VantageCloud
Teradata
Teradata VantageCloud is a cloud-native data warehouse platform built for enterprise-scale analytics. It unifies structured and semi-structured data across multi-cloud and hybrid environments, enabling high-performance querying, advanced analytics, and AI/ML integration. VantageCloud supports ANSI SQL, open data formats, and seamless interoperability with modern data tools—reducing vendor lock-in. Its scalable architecture handles complex workloads with built-in governance, making it ideal for organizations seeking a flexible, secure, and future-ready data warehouse solution. -
2
Google Cloud BigQuery
Google
As a fully managed data warehouse solution, BigQuery allows businesses to store and analyze large volumes of data in a secure, scalable environment. Its serverless architecture eliminates the need for infrastructure management, enabling users to focus on data analysis instead of system maintenance. BigQuery’s highly efficient query engine ensures fast performance even with massive datasets, making it ideal for organizations of all sizes. New customers receive $300 in free credits, giving them the opportunity to test BigQuery’s features and determine how it can support their data storage and analytics needs. The platform’s ability to scale effortlessly makes it particularly well-suited for dynamic, high-growth organizations.Starting Price: Free ($300 in free credits) -
3
Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2 compute/month -
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Amazon Redshift
Amazon
More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.Starting Price: $0.25 per hour -
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OpenText Analytics Database is a high-performance, scalable analytics platform that enables organizations to analyze massive data sets quickly and cost-effectively. It supports real-time analytics and in-database machine learning to deliver actionable business insights. The platform can be deployed flexibly across hybrid, multi-cloud, and on-premises environments to optimize infrastructure and reduce total cost of ownership. Its massively parallel processing (MPP) architecture handles complex queries efficiently, regardless of data size. OpenText Analytics Database also features compatibility with data lakehouse architectures, supporting formats like Parquet and ORC. With built-in machine learning and broad language support, it empowers users from SQL experts to Python developers to derive predictive insights.
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Apache Druid
Druid
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures. -
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Lyftrondata
Lyftrondata
Whether you want to build a governed delta lake, data warehouse, or simply want to migrate from your traditional database to a modern cloud data warehouse, do it all with Lyftrondata. Simply create and manage all of your data workloads on one platform by automatically building your pipeline and warehouse. Analyze it instantly with ANSI SQL, BI/ML tools, and share it without worrying about writing any custom code. Boost the productivity of your data professionals and shorten your time to value. Define, categorize, and find all data sets in one place. Share these data sets with other experts with zero codings and drive data-driven insights. This data sharing ability is perfect for companies that want to store their data once, share it with other experts, and use it multiple times, now and in the future. Define dataset, apply SQL transformations or simply migrate your SQL data processing logic to any cloud data warehouse.
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