Databricks Genie CodeDatabricks
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Related Products
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About
Genie Code is an AI agent built for data teams that analyzes, builds, and maintains complex data workflows inside the Databricks workspace. It autonomously plans and executes multistep tasks while adapting to an organization’s data and governance model, with specialized capabilities across data engineering, data science, machine learning, and business intelligence. Grounded in Unity Catalog metadata, semantics, and governance, it can identify authoritative tables, metrics, and assets, understand dependencies across data and AI systems, and respect existing access controls. For data science, Genie Code can find and clean data, explore datasets, test hypotheses, and generate shareable reports. Machine learning workflows include feature engineering, model training and evaluation, deployment, endpoint configuration, and performance tuning. Data engineers can use natural language to automate ETL workloads, optimize queries, and build Spark Declarative Pipelines.
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About
Managed Service for Apache Spark is a Google Cloud solution that simplifies running Apache Spark workloads with either serverless execution or fully managed clusters. It allows users to process large-scale data without needing to manage infrastructure, reducing operational complexity. The platform features Lightning Engine, which accelerates Spark performance by up to 4.9 times compared to open-source Spark. It supports data engineering, data science, and machine learning workflows at scale. Integration with Gemini enables AI-powered development, including automated code generation and troubleshooting. The service works seamlessly with open data formats like Apache Iceberg and integrates with tools like BigQuery and Knowledge Catalog. It offers flexible deployment options to suit different workloads and use cases. Overall, it provides a faster, smarter, and more efficient way to run Spark workloads in the cloud.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Data engineers, data scientists, ML engineers, and analytics teams seeking to automate complex data, machine learning, pipeline, and BI workflows
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Audience
Data engineers, data scientists, and enterprises looking for a scalable, high-performance, and low-maintenance platform to run Apache Spark workloads and modernize data processing pipelines
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationDatabricks
Founded: 2013
United States
www.databricks.com/product/genie/code
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Company InformationGoogle
Founded: 1998
United States
cloud.google.com/products/managed-service-for-apache-spark
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AlternativesNo Alternatives
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Categories |
Categories |
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Big Data Features
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Analysis Features
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
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Integrations
Ascend
Collibra
Databricks
Google Cloud BigQuery
Google Cloud Bigtable
Google Cloud Confidential VMs
Google Cloud GPUs
Google Cloud Knowledge Catalog
Google Cloud Managed Service for Apache Airflow
Google Cloud Profiler
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Integrations
Ascend
Collibra
Databricks
Google Cloud BigQuery
Google Cloud Bigtable
Google Cloud Confidential VMs
Google Cloud GPUs
Google Cloud Knowledge Catalog
Google Cloud Managed Service for Apache Airflow
Google Cloud Profiler
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