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SQreamDB

A SQL database that empowers organizations to perform complex analytics on petabyte-scale of data and gain time-sensitive business insights, faster and at one tenth of the cost.

SQreamDB is a game-changer for businesses struggling with overwhelming data volumes, complex queries, and sluggish processing times. This innovative platform leverages the raw power of Graphics Processing Units (GPUs) to accelerate data analysis at a fraction of the cost of traditional systems. SQreamDB is a powerful, high-performance SQL database designed for big data analytics. By leveraging GPU technology, SQreamDB enables organizations to analyze massive datasets quickly and cost-effectively. It is ideal for industries such as telecommunications, financial services, healthcare, and more.

What is SQreamDB?

SQreamDB is a relational database management system (RDBMS) built for the big data era. Unlike conventional RDBMS that rely on CPUs, SQreamDB harnesses the parallel processing capabilities of GPUs to deliver unmatched performance for complex SQL queries on even petabyte-scale datasets.

Benefits

Faster Time to Insights

Gain valuable business intelligence from your data in real-time, enabling quicker decision-making.

Improved Operational Efficiency

Optimize resource utilization and streamline data analysis processes.

Enhanced AI and Machine Learning

Fuel your AI and machine learning initiatives with high-performance data access.

Reduced Risk and Errors

Make data-driven decisions with confidence thanks to faster and more accurate insights.

Simplified Management

SQreamDB cuts through complex data prep, reducing errors and streamlining data handling.

Real-Time Insights

Get insights from live data streams with SQreamDB’s blazing speed, enabling proactive decisions.

Lower Latency

Experience faster data retrieval and quicker query responses with SQreamDB’s reduced data latency.

Enhanced Security

SQreamDB safeguards your data with features like access control, encryption, and auditing.

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Features

Query

Processing is performed by using the ANSI-SQL syntax. Running queries can be done through the built-in SQream Acceleration Studio, or through a third-party BI tool.

Connectivity

SQream integrates into existing ecosystems, with support for industry-standard ODBC and JDBC connectors, as well as Python and C# .Net, C++, Java, and others.

Parallelism

OptimCampaign can be integrated to work with other marketing databases and campaign management systems to help marketers achieve the next level of optimized campaigns. 

Compression

All the data that is it ingested is automatically compressed at a 5:1 ratio

Architecture

The compute and storage are completely separated, with multiple compute units, running to store or retrieve data from a single or multiple storage sources. This concept provides flexibility and easy scaling, while data processing is being done not in memory.

Performance

Acceleration leans on synchronizing all available resources (CPU, GPU, RAM) for complex analytical tasks while performing automatic vertical and horizontal partitioning of the data. moreover, it stores data tables by columns, therefore eliminating unnecessary reading for each analytical workload.

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Product highlights

  • Data Warehouse

    Store and manage enterprise-scale data, so decision-makers, business analysts, data engineers, and data scientists can analyze the data and gain valuable insights from BI, SQL clients, and other analytics apps.

  • Data Preparation

    Transform raw data through denormalization, pre-aggregation, feature generation, cleaning, and BI processes, so it can be ready for Machine Learning and AI processes.

  • Query Engine

    Analyze data from any source, in any technology, and in any format, on top of existing analytical solutions and without any data duplication required.

Case Studies

Telecom​

AIS Thailand turns billions of records of siloed data into better network management.

Manufacturing

Electronics giant improves yield from 50% to 90%.

Telecom

Cloud comms provider responds to 40,000+ customer queries a day.

Resources

Datasheet

Check out this datasheet to learn more about SQreamDB.

Documentation

Get the latest technical details about SQreamDB.

Dig Deeper

Learn more about the Machine Learning use cases of SQreamDB.

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FAQs

SQreamDB is a relational database management system (RDBMS) designed for big data analytics. It leverages GPUs for faster processing of massive datasets and uses familiar SQL for querying data.

  • Speed: SQreamDB utilizes GPUs to achieve significantly faster query speeds on large datasets compared to traditional RDBMS.
  • Scalability: SQreamDB can handle petabyte-scale data and scales horizontally for concurrent users.
  • Cost-effective: SQreamDB offers competitive pricing compared to other big data analytics tools.
  • Ease of use: Existing SQL knowledge can be applied for querying data in SQreamDB.

No, SQreamDB is a commercial product with different licensing options available.

SQreamDB supports a wide range of data types, including integers, floating-point numbers, strings, dates, and more

SQreamDB stores data in a columnar format, which is optimized for faster analytics queries

SQreamDB offers recommendations for hardware configurations based on the number of users, data size, and desired performance

Yes, SQreamDB provides security features such as user roles and permissions, secure access protocols, and encryption options.

SQreamDB offers installation guides for various operating systems, including Docker containers

Yes, SQreamDB provides comprehensive documentation covering installation, usage, configuration, and best practices

See SQreamDB in Action

Schedule a custom demo to discover how SQreamDB works.

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