Data is the lifeblood of innovation and growth in today’s enterprise landscape. Yet, as organizations scale their analytics, AI, and machine learning initiatives, they find themselves mired in complexity. Traditional Hadoop-based ecosystems, multi-layered data lake architectures, and an ever-growing patchwork of table formats, catalogs, and query engines have created a daunting operational challenge.
While open formats like Apache Iceberg have introduced greater flexibility for data management, they still rely on multiple layers of infrastructure—object storage, separate catalogs, and orchestrations of different processing engines. The result is often a system that’s technically open but operationally cumbersome.
Meanwhile, business leaders are demanding real-time insights, model training at scale, and the ability to support more users and workloads without compromising performance. The question becomes: how can we achieve the speed and simplicity of a tightly integrated system without sacrificing choice?
The VAST Perspective: Beyond the Status Quo
At VAST Data, we’ve watched organizations struggle to piece together a functional data technology stack, only to end up with a complex hodgepodge of components that require constant tuning, integration work, and troubleshooting. Open table formats solved one problem—freeing data from proprietary storage lock-in—yet introduced others, such as inconsistent performance and complex operations.
The time has come to move beyond the status quo. Instead of juggling disjointed layers and tools, Vast believes you should unify them. Why not bring high-performance storage, advanced data management, and broad ecosystem compatibility under one roof?
This is the heart of VAST Data’s philosophy. We’re reimagining what it means to run a modern data architecture by focusing on simplicity, raw performance, and integrated choice. Our goal is to help data teams to accelerate their analytical workflows without getting bogged down in the complexities that plague traditional and hybrid stacks.
Understanding VAST DataBase Capabilities
At the core of our vision is VAST DataBase—a tightly integrated set of capabilities that pairs high-performance, all-flash storage with schema-aware data management. Instead of scattering data across different stores and formats, customers can now maintain a streamlined data stack optimized for large-scale analytics, BI, AI, and streaming use cases.
VAST DataBase combines the raw speed of VAST’s disaggregated, shared-everything (DASE) architecture with the intelligence to handle structured and semi-structured data efficiently to deliver real-time analytics across all your data. With VAST, you can access and analyze your data using your preferred analytics engines, like Trino, Spark, Dremio, and Kafka, enabling a single, cohesive environment for running everything from batch analytics to real-time streaming pipelines.
This synergy means you can run your data pipelines, queries, and models directly against a platform built for speed and scale—no more spending cycles on endless tuning and system assembly. The result? Faster insights, simpler operations, and a smoother path to turn data into competitive advantage.
Differentiation Points: VAST vs. Open Table Formats
1. Performance at Scale: Unlike table formats that sit atop generic object storage, VAST DataBase benefits from an end-to-end integration made possible by our innovative DASE architecture and data model, built from the ground up. The result is a transactional data warehouse hyper-optimized for NVMe that is capable of running at unmatched speed, eliminating latency and bottlenecks, and delivering consistent, predictable performance as workloads scale. We have seen 300% performance increases as compared to HDFS and solutions built on S3.
2. Simplicity Over Assembly:
Open table formats promise flexibility, but they often come with the hidden cost of assembling and maintaining a complex data pipeline ecosystem. With VAST, you get a streamlined solution—no need for separate storage systems, complex catalogs, or multi-layer orchestration. We reduce operational overhead so you can focus on extracting value from data.
3. Cost-Efficiency and Operational Savings: Managing disjointed systems and tuning them for performance drives up costs over time. By consolidating the data management layer and providing native integrations, VAST lowers total cost of ownership. Reduced complexity translates directly into management efficiency, fewer maintenance headaches, and ultimately, more predictable budgets.
4. Future-Proof Flexibility: While VAST delivers a unified solution, we still embrace open standards and popular analytics engines. This means you’re never forced into using proprietary query languages or tools. You retain the flexibility to choose the technologies that best fit your evolving needs—without sacrificing performance or simplicity.
Real-World Scenario
Consider a multinational bank grappling with delivering real-time insights to its frontline decision-makers and risk analysts. In many instances, the data environment consists of object storage for raw transaction logs, a separately maintained table format layer for structuring that data, and multiple analytics engines connected for running risk assessments, compliance checks, and customer segmentation. This approach often requires constant fine-tuning of siloed components, cumbersome metadata management, and slow query performance—all of which hinder proactive risk management and timely identification of growth opportunities. Additionally, this layered architecture can force unnecessary replication of data across multiple environments, eroding trust in its accuracy and increasing overall risk as disparate copies fall out of sync.
The VAST Data Platform fundamentally reshapes this process. By consolidating a bank’s data architecture, it’s possible to reduce query times dramatically, enabling near-instant access to critical transaction data. Risk analysts can explore market fluctuations and compliance signals interactively—rather than waiting overnight for batch processes—while data scientists can accelerate model training workflows, liberated from I/O bottlenecks and file format complexities. IT teams, previously bogged down with continuous operational overhead, can redirect their energy toward strategic initiatives and long-term innovation.
This transformation isn’t unique to one financial institution. Across the banking sector and beyond, consolidating the data platform delivers tangible results: enhanced agility, faster insights, and a simpler, more responsive path to meeting regulatory demands and customer expectations.
Embracing an Integrated Future
As the data landscape evolves, so do the expectations for what a data platform should deliver. At VAST Data, we see a future where data architecture is no longer a patchwork of disparate technologies. Instead, it’s a unified, high-performance data management solution that effortlessly supports a wide range of analytical and AI/ML workloads.
We’re committed to continuous innovation, adding more integrations, enhancing data management features, and working with the broader community to ensure interoperability and openness. Our vision is to eliminate the false compromise among performance, cost, and scale. With VAST, you can achieve all three.
Conclusion
The era of complexity and compromise is ending. VAST Data provides a platform that delivers the blistering performance you need and the simplicity you crave, all while preserving the freedom to run the tools and engines you prefer.
If you’re ready to experience a new way of managing and leveraging your data—one that simplifies operations, boosts performance, and empowers innovation—get in touch with us at vastdata.com. Request a demo, explore our documentation, or talk to customers who’ve already transformed their data environments with VAST.
