Supercharge
Your Data Lake
with Spark 3.3
Qubole’s multi-engine data lake fuses ease of use with cost-savings.
Now powered by Spark 3.3, it’s faster and more scalable than ever.
You’re handling massive datasets and can’t afford the time or cost of processing slowdowns. So, how can you ensure your business can deliver results without breaking the bank?
Try switching to Spark 3.3 on Qubole’s Open Source Data Lake. With new features like Bloom Filter Joins and AQE improvements, Spark 3.3 on Qubole is significantly faster and more scalable than its predecessors, with the stability needed for modern workloads.
Unlock insights & improved user experience with Spark 3.3 and Jupyter Notebook on Qubole. Harness the synergistic power of Spark 3.3 and Jupyter Notebooks. When integrated, they are an ideal match for AI/ML applications that work harder than the sum of their parts for enhanced data processing capabilities and interactive analytics your project needs.
Goodbye, Performance Issues.
Save 42% on data lake costs with Spark 3.3 on Qubole*
Apache Spark 3.3 Benefits
Costs
Advanced cost controls result in up to a 42% reduction in costs with Qubole
Performance
Performance optimizations and smart management tools that increase Spark efficiency
New Features
Performance optimizations and smart management tools that increase Spark efficiency
Scalability
Expand your data projects scope more easily, and with fewer errors
Expertly Tested,
CDO-Approved.
Your data environment needs safeguarding: anyone who has been burned before when implementing ‘the latest and greatest’ too quickly can attest to this.
That’s why we exhaustively test in the Qubole environment before launching new releases. You can start using Spark 3.3 confidently because we’ve looked for the issues and found solutions, meeting all GDPR and CCPA compliance requirements.
AI Enablement with
Spark 3.3 on Qubole
Harmonized Technology
Spark 3.3 and Jupyter Notebooks unite to deliver accelerated insights and a seamless user experience in AI/ML workflows.
Streamlined Innovation
Spark 3.3 on Qubole simplifies the ML lifecycle, from data preprocessing to model deployment, enhancing productivity and innovation.
Future-Ready Framework
Anticipating the evolution of big data, Qubole is committed to scaling, cloud adaptability, & supporting the continuous growth of ML models.
Spark 3.3 Technical Features
Bloom
Filter Joins
Bloom filters greatly improve join query performance, by reducing data shuffle and computation needs for up to 10x faster join query performance.
Query Execution
Enhancements
Adaptive query execution improvements, such as optimizing one-row query plans and eliminating limits for faster query executions and more efficient data processing.
New Built-in
Functions
A new range of functions featuring linear regression, statistical/string processing and encryption functions. Enhanced security, compatibility, and API features.
Migration
Capabilities
Increased ANSI SQL compliance, support for new interval data types and implicit casting in ANSI mode make migration easier from traditional data warehouses.
An open and secure multi-cloud data lake platform for machine learning, streaming analytics, data exploration and ad-hoc analytics.
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