The SQream Platform

In the cloud, private cloud or on-prem, you can count on SQream to lower your data expenses while increasing performance. Experience the power of SQL on GPU.

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Built for AI / ML / Data Workloads

Harness AI and Machine Learning Workflowswith GPU-Accelerated SQL

In the cutting-edge realm of artificial intelligence (AI) and machine learning (ML), the ability to process and analyze large datasets quickly is crucial for developing accurate models and algorithms. SQream is meticulously engineered to meet these demands, providing a robust foundation for your AI and ML projects. With the pioneering propriety SQL on GPU technology, our platform's exceptional speed and efficiency in handling complex queries and massive datasets ensure that data scientists and AI researchers can iterate and refine their models faster than ever before.

High Performance, Massive Datasets, lower cost

Analyze Terabytes to Petabytes of Data

In the era of big data, the ability to process petabyte-scale datasets efficiently is not just an advantage — it's a necessity. SQream is engineered to handle the vast volumes of data that modern businesses generate, delivering high-performance analytics without compromising speed. Our innovative use of GPU technology not only accelerates data processing but also significantly reduces the physical footprint and energy consumption of your data center, making SQream the smart choice for environmentally conscious, cost-effective data analytics.

Flexible Deployment: In the Cloud or On-Premises

Deploy Wherever Your Data Lives

Flexibility is key in today’s diverse IT environments. SQream offers unparalleled adaptability, allowing you to deploy our platform either in the cloud or on-premises, based on your operational needs and data governance requirements. Whether you're leveraging cloud computing for its scalability and cost-efficiency or utilizing on-premises installations for enhanced control and security, SQream integrates seamlessly into your existing infrastructure, ensuring your data analytics capabilities are always optimized.

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Simple Integration

Effortless Integration with Your Existing Data Stack

SQream is designed for simplicity, ensuring you can integrate our platform into your existing data ecosystem with minimal effort. Our technology is built to be compatible with a wide array of data sources, BI tools, and data formats. This means you can start analyzing your data faster, without the tedious data migration projects that typically slow down analytics initiatives. With SQream, your path to insights is straightforward and uncomplicated, letting you focus on what matters most — unlocking the value within your data.

Complex Queries at Unprecedented Speeds

Unlock Insights from Your Most Demanding Data

Complex queries no longer need to be a bottleneck in your analytics workflow. SQream excels at executing intricate SQL queries on large datasets at speeds that set new industry benchmarks. This capability enables deeper, more detailed analysis of your data, uncovering insights that were previously inaccessible due to computational limitations. With SQream, you can push the boundaries of data exploration, asking the critical questions that drive innovation and strategic growth.

Dynamic Scalability

Scale Effortlessly with Your Data

As your data grows, so does SQream. Designed with dynamic scalability in mind, SQream allows you to scale up or out seamlessly without interrupting your analytics workflows. This ensures that your data processing capabilities can evolve with your business needs, providing flexibility and eliminating the common bottleneck of data infrastructure scalability.

Optimized Data Compression

Maximize Storage Efficiency

SQream utilizes advanced data compression techniques to maximize storage efficiency and reduce costs. By efficiently compressing data without sacrificing query performance, SQream enables organizations to store more data at a lower cost. This optimization of storage resources makes it feasible to maintain extensive historical data for deep analytics.