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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Harness the power of your data and create innovative artificial intelligence (AI) solutions using Azure Databricks, where you can establish your Apache Spark™ environment in just minutes, enable autoscaling, and engage in collaborative projects within a dynamic workspace. This platform accommodates multiple programming languages such as Python, Scala, R, Java, and SQL, along with popular data science frameworks and libraries like TensorFlow, PyTorch, and scikit-learn. With Azure Databricks, you can access the most current versions of Apache Spark and effortlessly connect with various open-source libraries. You can quickly launch clusters and develop applications in a fully managed Apache Spark setting, benefiting from Azure's expansive scale and availability. The clusters are automatically established, optimized, and adjusted to guarantee reliability and performance, eliminating the need for constant oversight. Additionally, leveraging autoscaling and auto-termination features can significantly enhance your total cost of ownership (TCO), making it an efficient choice for data analysis and AI development. This powerful combination of tools and resources empowers teams to innovate and accelerate their projects like never before.

Description

Managed Service for Apache Spark is a unified Google Cloud platform designed to run Apache Spark workloads with greater ease, performance, and scalability. It offers both serverless and fully managed cluster deployment options, allowing users to choose the best model for their needs. The platform eliminates the need for infrastructure management, enabling teams to focus on data processing and analytics. With Lightning Engine, it delivers up to 4.9x faster performance than open-source Spark, improving efficiency for large-scale workloads. It integrates AI-powered tools like Gemini to assist with code generation, debugging, and workflow optimization. The service supports open data formats such as Apache Iceberg and connects seamlessly with Google Cloud services like BigQuery and Knowledge Catalog. It is designed for a wide range of use cases, including ETL pipelines, machine learning, and lakehouse architectures. Built-in security features and IAM integration ensure strong data governance. Flexible pricing models allow users to pay based on job execution or cluster uptime. Overall, it helps organizations modernize their data infrastructure and accelerate analytics workflows.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Openbridge Yes 
definity Yes 
Ascend No 
Bluemetrix Yes 
Captain Compliance Yes 
DQOps Yes 
Data Commerce Cloud Yes 
Datagaps ETL Validator Yes 
Embeddable Yes 
EquityZen Yes 
Google Cloud Confidential VMs No 
Hackolade Yes 
Horovod Yes 
IBM watsonx.data integration No 
Immuta No 
Nuvento Yes 
Protegrity Yes 
Tokern No 
Tonic Ephemeral Yes 
just words Yes 

Integrations

Openbridge Yes 
definity Yes 
Ascend Yes 
Bluemetrix No 
Captain Compliance No 
DQOps No 
Data Commerce Cloud No 
Datagaps ETL Validator No 
Embeddable No 
EquityZen No 
Google Cloud Confidential VMs Yes 
Hackolade No 
Horovod No 
IBM watsonx.data integration Yes 
Immuta Yes 
Nuvento No 
Protegrity No 
Tokern Yes 
Tonic Ephemeral No 
just words No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/services/databricks/

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/products/managed-service-for-apache-spark

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Product Features

Big Data

Collaboration Yes 
Data Blends Yes 
Data Cleansing No 
Data Mining Yes 
Data Visualization Yes 
Data Warehousing Yes 
High Volume Processing Yes 
No-Code Sandbox No 
Predictive Analytics Yes 
Templates No 

Data Analysis

Data Discovery Yes 
Data Visualization Yes 
High Volume Processing Yes 
Predictive Analytics Yes 
Regression Analysis Yes 
Sentiment Analysis Yes 
Statistical Modeling Yes 
Text Analytics No 

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