Skip to content


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 SQL database designed for big data analytics. It allows organizations to analyze petabyte-scale data using standard SQL queries and gain insights faster and at a lower cost. SQreamDB integrates with existing data ecosystems and uses GPUs for parallel processing and data compression to achieve high performance. Overall, SQreamDB offers a powerful and user-friendly solution for organizations seeking to unlock valuable insights from massive datasets, enabling faster, more informed decision-making at a significantly lower cost.

Product highlights


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.


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.


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


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


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.


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.

Asking Bigger with SQreamDB

  • 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


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


Electronics giant improves yield from 50% to 90%.


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

See SQreamDB in Action

Schedule a custom demo to discover how SQreamDB works.

Please enter you email to view this content.