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Turbocharging Data Analytics with KX on Databricks
Data analysts know, that […]
KX for Databricks
Accelerating time-series workloads on Databricks
Bringing ultra-real-time analytics to Databricks’ Lakehouse platform
Move faster than your competitors by setting a new standard in quantitative research, data modeling, and trading analysis. Our collaboration with Databricks combines our expertise in handling time-series data with their comprehensive compute and machine learning frameworks.
High performance processing
Enable time-series analytics within existing Databricks pipelines with no external dependencies or q expertise.
Accelerate time-to-market
Manage and analyze temporal data to improve modeling or trading strategies.
Seamless analysis
Seamlessly run Python and Spark workloads on datasets natively stored in Delta Lake for unparalleled data analysis and insights.
Simplified data management
Support for multiple data formats and comprehensive governance, make it easier to manage and analyze large datasets.
Why KX for Databricks?
Optimize query speed
Highly performant engine enables faster processing of data ingestion and queries for real-time insights.
Enhance quant research
Deliver the sophisticated analytical tools necessary for advanced quant research and data analysis capabilities.
Handle high-volume streaming
Stream large volumes of data from multiple digital channels to enhance real-time analysis and actionable insights.
Want to learn more?
For more information about our partnership with Databricks, reach out to our sales team.
