Best Data Warehouse Software for Data Virtuality
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Compare the Top Data Warehouse Software that integrates with Data Virtuality as of December 2025
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This a list of Data Warehouse software that integrates with Data Virtuality. Use the filters on the left to add additional filters for products that have integrations with Data Virtuality. View the products that work with Data Virtuality in the table below.
What is Data Warehouse Software for Data Virtuality?
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 Data Virtuality 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 -
4
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 -
5
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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6
IBM Db2
IBM
IBM Db2 is a family of data management products, including the Db2 relational database. The products feature AI-powered capabilities to help you modernize the management of both structured and unstructured data across on-premises and multicloud environments. By helping to make your data simple and accessible, the Db2 family positions your business to pursue the value of AI. Most of the Db2 family is available on the IBM Cloud Pak® for Data platform, either as an add-on or an included data source service, making virtually all of your data available across hybrid or multicloud environments to fuel your AI applications. Easily converge your transactional data stores and rapidly derive insights through universal, intelligent querying of data across disparate sources. Cut costs with the multimodel capability that eliminates the need for data replication and migration. Enhance agility by running Db2 on any cloud vendor. -
7
Cloudera
Cloudera
Manage and secure the data lifecycle from the Edge to AI in any cloud or data center. Operates across all major public clouds and the private cloud with a public cloud experience everywhere. Integrates data management and analytic experiences across the data lifecycle for data anywhere. Delivers security, compliance, migration, and metadata management across all environments. Open source, open integrations, extensible, & open to multiple data stores and compute architectures. Deliver easier, faster, and safer self-service analytics experiences. Provide self-service access to integrated, multi-function analytics on centrally managed and secured business data while deploying a consistent experience anywhere—on premises or in hybrid and multi-cloud. Enjoy consistent data security, governance, lineage, and control, while deploying the powerful, easy-to-use cloud analytics experiences business users require and eliminating their need for shadow IT solutions. -
8
VMware Tanzu Greenplum
Broadcom
Free your apps. Simplify your ops. To win in business today, you have to be great at software. How do you improve feature velocity on the workloads that power your business? Or effectively run and manage modernized workloads on any cloud? VMware Tanzu—coupled with VMware Pivotal Labs—enables you to transform your teams and your applications, while simplifying operations across multi-cloud infrastructure: on-premises, public cloud, and edge.
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