Top 10 Data Virtualisation Platforms

The Denodo Platform is a specialist data virtualisation provider offering a logical data management platform for integrating and delivering distributed enterprise data.

The platform creates a unified data access and semantic layer across data warehouses, lakehouses, operational databases, SaaS applications, APIs and files. It provides live access to data without requiring every dataset to be copied into a central, unified repository.

Denodo also provides query optimisation, caching, governance and data delivery capabilities. Centralised policies and semantic context help organisations provide consistent information to BI tools, enterprise applications and AI systems.

Best suited: Large organisations that require enterprise-wide data virtualisation, governed self-service access and integration across complex hybrid environments.

Check out our Denodo's whitepaper on data virtualisation's benefits.

Formerly known as TIBCO Data Virtualization, Spotfire Data Virtualization creates virtual tables (aka logical views) that integrate and secure information from different data sources.

The platform enables organisations to design reusable data services without requiring consumers to understand where the underlying information is stored. It includes query, metadata, governance and security capabilities, as well as adapters for cloud storage and enterprise data systems.

Those organisations already using Spotfire analytics or other products in the Cloud Software Group portfolio may find this integration particularly relevant to their operations.

Best suited: Enterprises that need governed logical data services across diverse cloud and on-premises sources.

SAP Datasphere combines data integration, cataloguing, semantic modelling, warehousing, federation and virtualisation within a cloud-based data service.

The platform can connect SAP and non-SAP data while simultaneously preserving business context and logic. Its virtualisation capabilities allow teams to access remote information without needing to replicate it within SAP Datasphere.

Best suited: Organisations that rely heavily on SAP applications and want to combine SAP and third-party data within a governed business data layer.

IBM Data Virtualization provides a universal query engine for accessing databases, warehouses, data lakes and streaming sources without manually moving or replicating all the underlying information.

The platform creates unified virtual views across distributed systems and includes intelligent caching to support query performance.

It also integrates with IBM’s cataloguing and governance capabilities, helping organisations apply consistent controls to information accessed through the virtual layer.

Best suited: Organisations using IBM’s data and AI ecosystem or requiring governed access across hybrid data environments.

This product was previously known as Data Virtuality. CData acquired the company in 2024 and now markets the platform as CData Virtuality.

CData Virtuality combines data virtualisation with optional data replication capabilities. It can unify information from cloud applications, databases and on-premises systems through a shared logical layer.

The platform allows organisations to query distributed data without automatically moving or duplicating it. Where performance or availability requirements make live querying impractical, teams can use materialisation or replication selectively.

Best suited: Organisations that want to combine live data access and selective replication within one integration environment.

AtScale provides a universal semantic layer that presents enterprise data using consistent, business-friendly definitions across BI and analytics tools.

Its virtualisation capabilities abstract the complexity of underlying cloud data platforms. Users can work with governed metrics and multidimensional models without creating a separate extract for every tool or use case. AtScale also supports query acceleration and calculations across large cloud datasets.

AtScale is more specialised than your average general-purpose data virtualisation platform. Its primary focus is providing consistent business metrics and semantic models for analytics.

Best suited: Enterprises that want a governed semantic layer across multiple BI tools and cloud data platforms.

Informatica Intelligent Data Management Cloud provides data integration, cataloguing, governance, quality and delivery capabilities within a broad cloud data management platform.

Its data access and integration services can help organisations discover, connect and deliver information across cloud and on-premises platforms.

Informatica is broader than a dedicated data virtualisation tool, making it suited for organisations that want virtualisation-related capabilities with the added benefits of wider enterprise data management functions.

Best suited: Large organisations looking for data integration, governance and quality capabilities within a comprehensive enterprise data management environment.

Dremio's Agentic Lakehouse Platform provides a SQL query and semantic layer across data held in object storage, lakehouses, warehouses and databases.

Its architecture enables users and applications to query distributed information through a unified access layer. Semantic modelling, query acceleration and workload management can help make large datasets available to BI and analytics tools without creating a separate extract for every use case.

Although Dremio is generally categorised as a lakehouse platform rather than a traditional standalone data virtualisation product, its federated-query and logical-data-layer capabilities address many of the same requirements.

Best suited: Organisations building open lakehouse environments that need self-service SQL access and query acceleration across distributed data.

Starburst Enterprise's data virtualisation offering is a distributed SQL query platform based on Trino. It allows teams to query information across data lakes, warehouses and other systems without first consolidating every dataset.

The platform supports federated queries, data products and access controls across distributed environments. It can reduce the need for additional data pipelines when analysts must combine information from several platforms.

Starburst is not always seen or described as a traditional data virtualisation suite. However, its ability to query and combine data where it resides makes it relevant to organisations evaluating modern virtualisation and federation approaches.

Best suited: Enterprises that need high-performance distributed SQL across open, hybrid or multicloud data environments.

CData Connect AI provides a managed cloud layer for accessing information held in SaaS applications, databases and cloud services.

The platform converts different source formats into a consistent tabular model. Teams can create reusable views, run federated queries and connect live data to BI, spreadsheet, development and AI tools.

Its emphasis on SaaS connectivity distinguishes it from traditional data virtualisation products originally designed for databases and on-premises systems. Centralised access controls allow administrators to govern connections and user access from one environment.

Best suited: Organisations that need managed, real-time access to data distributed across SaaS and cloud applications.