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Enterprise Layer Intelligence
Categories/Data Platform & Integration/Xonai
Xonai

Xonai

Founded 2021

Accelerate Apache Spark queries and cut cloud compute costs without rewriting code

You can use Xonai FuseCore to accelerate Apache Spark workloads and lower cloud computing expenses without altering your existing pipelines. It functions as a drop-in plugin powered by an MLIR JIT compiler that speeds up query execution directly in process. You install the JAR file, turn on a configuration flag, and run data transformations without migrating systems or modifying queries. It works within your current security setup across Amazon EMR, Databricks, and Google Cloud Dataproc, cutting processing times for compute-heavy joins, aggregations, and sorting jobs.

What Xonai does

Speed up long-running Apache Spark queriesLower cloud infrastructure compute costs for big data pipelinesDeploy a drop-in acceleration plugin via spark-submitExecute complex SQL joins and aggregations with reduced CPU timeProcess large analytical datasets without migrating platformsCut memory pressure during heavy data transformation jobsMLIR JIT compiler executing code directly in-processZero code changes with drop-in JAR compatibilityCompatibility with open-source Spark, Amazon EMR, Databricks, and DataprocLocal execution keeping data inside your existing infrastructureSingle configuration flag activation via spark-submitHardware acceleration without requiring specialized siliconPreserves all existing Spark APIs, libraries, and query logic

Frequently asked

Apache SparkApache SparkDatabricksDatabricks

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Xonai FuseCore, Apache Spark, query acceleration, MLIR compiler, big data, Spark plugin, Amazon EMR, Databricks, Google Dataproc, cloud compute costs, data processing, Spark SQL, ETL acceleration, JIT compilation, in-process execution