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DBMS > SQream DB

SQream DB System Properties

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Editorial information provided by DB-Engines
NameSQream DB
Descriptiona GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Rank#235  Overall
#108  Relational DBMS
Technical documentationdocs.sqream.com
DeveloperSQream Technologies
Initial release2017
Current release2022.1.6, December 2022
License infoCommercial or Open Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, CUDA, Haskell, Java, Scala
Server operating systemsLinux
Data schemeyes
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Types
Secondary indexesno
SQL infoSupport of SQLyes
APIs and other access methods.Net
Supported programming languagesC++
JavaScript (Node.js)
Server-side scripts infoStored proceduresuser defined functions in Python
Partitioning methods infoMethods for storing different data on different nodeshorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyes
More information provided by the system vendor
SQream DB
Specific characteristics

SQream allows companies to get answers from its data and get new business-insights that were unattainable before at an exceptional speed. 

SQreamDB is an SQL database that is utilizing GPUs in order to get faster insights on more data.

SQreamDB is optimized for big data analytics at a petabyte scale. Its GPU-based technology is optimized for executing multiple simple operations and tasks at the same time. SQream is not running only on the GPU, but offloading the most complicated tasks at every query.  

SQreamDB can be used as a traditional data warehouse, as well as serve for complex data preparation use cases or as a query engine above a data lake. 

SQreamDB is an on-prem product and is also cloud-enabled for private clouds. 

Leading organizations in telecom, manufacturing, finance, and additional industries around the world use SQreamDB to accelerate business intelligence and gain more value from their data.

Competitive advantages
  • Scalability when processing bigger datasets. 

  • Faster business insights, with more complex queries. 

  • Lower TCO.

  • Less physical hardware.

  • Smaller carbon footprint.

Typical application scenarios

What can you do with 100x faster SQL analytics?

  • Better and more timely decision-making, on your most complicated and bigger business questions.

  • More reliable ML models.

  • Faster data preparation for ML models.

  • More personalized customer experience and increased loyalty

  • Optimized business and operational efficiency.


  • Customer 360
  • Competitive Analysis
  • Network Optimization


  • Fraud Analysis
  • Risk Consolidation
  • Customized Services


  • Peta-scale IoT analytics
  • Data silos consolidation


  • Monitor Competitors
  • Customer Experience
  • Operational Decisions
Key customers

Some of our customers include: LG-U+, AIS , ACL Mobile, Pubmatic, Telkomsel, LG Electronics


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Related products and services

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More resources
SQream DB
Recent citations in the news

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

In A Parallel Universe, Data Warehouses Run On GPUs
4 October 2018, The Next Platform

Stretching GPU Database Performance With Flash Arrays
26 February 2019, The Next Platform

Accelerated Databases In The Fast Lane
25 June 2020, The Next Platform

Beyond the Delta: Compression is a Must for Big Data
8 October 2018, insideBIGDATA

provided by Google News

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