Data acceleration platform SQream announced today the latest performance benchmarks for its cloud data solution, SQream Blue, raising the bar for industry standards in big data processing.
Started by the nonprofit Transaction Processing Performance Council (TPC), TPCx-BB is a benchmark for objectively comparing big data solutions.
During its comparison section, SQream Blue far exceeded the existing benchmark, handling 30 TB of data 3X faster and at 1/3 of the cost of Databricks’ Spark-based Photon SQL engine.
As part of the TPCx-BB assessment, SQream Blue handled tasks typically encountered in real-world scenarios, such as building a model to predict whether an online shopper would be interested in a given item category based on their online activities.
Said Matan Libis, VP Product at SQream, “Databricks users and analytics vendors can easily add SQream to their existing data stack, offload costly intensive data and AI preparation workloads to SQream, and reduce cost while improving time to insights.”
“In cloud analytics, cost performance is the only factor that matters. SQream Blue’s proprietary complex engineering algorithms offer unparalleled capabilities, making it the top choice for heavy workloads when analyzing structured data,” added the executive.
The company ran the benchmark on AWS, and tested against the data management solution Databricks. All generated data was stored as Apache Parquet files on Amazon S3.
During the comparison, SQream Blue’s total runtime was 2462.6 seconds, with the total cost for processing being $26.94. Databricks’ total runtime was 8332.4 seconds, at a cost of $76.94.
SQream Blue’s performance is credited to its ability to allocate resources to ensure workloads are handled most efficiently, and to its capacity to divide data processing between GPUs and CPUs. To learn more, visit here.