Dremio and VAST Data

Dremio and VAST Data have identified several key challenges that customers face when trying to leverage data for AI and analytics projects. They believe that these challenges are hindering organisations from achieving competitive advantage and driving business growth in the era of AI.

Data access and speed

• Customers often struggle with slow data access, which hinders the productivity of their analysts, data scientists, and engineers.

• The inability to quickly access and combine data from multiple sources slows down decision-making processes and the pace of AI and analytics projects.

• Dremio and VAST Data aim to solve this problem by providing a high-performance data platform that enables fast access to data, regardless of its source or format.

Data silos and complexity

• Enterprises typically have data scattered across multiple silos, such as databases, data warehouses, data lakes, and cloud storage.

• This fragmentation makes it difficult for users to access and combine data for analysis, as they need to navigate through various systems and perform complex data movement and transformation tasks.

• Dremio's data virtualization capabilities help break down these silos by providing a unified, virtual view of the data, allowing users to access and query data from multiple sources as if it were in a single dataset.

Cost and scalability

• As data volumes grow and more users require access to data for AI and analytics projects, the cost of storing and processing data can become a significant burden for organisations.

• Traditional data infrastructure often struggles to scale cost-effectively to meet the demands of modern AI and analytics workloads.

• VAST Data's high-performance, all-flash storage system is designed to provide cost-effective scalability for petabyte to exabyte-scale datasets, enabling organizations to store and process large volumes of data efficiently.

Accelerating AI and analytics projects

• Customers are under pressure to deliver AI and analytics projects faster to gain a competitive edge and drive business growth.

• However, the complexity of data infrastructure and the time spent on data preparation and movement often slow down the development and deployment of these projects.

• The combination of Dremio's data virtualization and VAST Data's high-performance storage aims to simplify the data infrastructure and accelerate AI and analytics projects by providing fast, easy access to data and eliminating the need for complex data movement and transformation processes.

To make data access better, Dremio and VAST Data's joint solution focuses on the following:

Data virtualization

• Dremio creates a semantic layer that abstracts the complexity of the underlying data sources, presenting a unified, virtual view of the data to users.

• This allows users to access and query data from multiple sources using familiar SQL tools, without having to worry about the physical location or format of the data.

• Data virtualization also enables users to combine data from different sources into a single virtual dataset, making it easier to perform cross-source analysis and gain insights.

High-performance storage

• VAST Data's all-flash storage system provides fast access to large volumes of structured, semi-structured, and unstructured data.

• By storing data in a high-performance, scalable storage platform, organizations can ensure that their analysts, data scientists, and engineers have quick access to the data they need for AI and analytics projects.

• The fast storage also enables real-time analytics and interactive queries, allowing users to explore and analyze data on the fly.

Simplified data architecture

• By combining Dremio's data virtualization with VAST Data's storage, the joint solution simplifies the data architecture, eliminating the need for complex data movement and transformation processes.

• This simplified architecture reduces the time and effort required to prepare data for analysis, enabling organizations to focus on deriving insights and building AI models instead of managing complex data pipelines.

Scalability and cost-efficiency

• VAST Data's storage system is designed to scale cost-effectively from petabytes to exabytes, allowing organisations to store and process large volumes of data without breaking the bank.

• Dremio's data virtualization layer also helps reduce costs by minimising the need for data movement and replication, as users can query data directly from the source without having to move it to a separate system.

In summary, Dremio and VAST Data believe that by providing fast, easy access to data through data virtualization and high-performance storage, they can help customers overcome the challenges of slow data access, data silos, and cost scalability.

Their joint solution aims to accelerate AI and analytics projects by simplifying the data architecture and enabling users to focus on deriving insights and building AI models, rather than grappling with complex data infrastructure.