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ease
features
design
support

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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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Openbridge
definity
AnalyticsCreator
Ango Hub
Ascend
Azure Data Lake
Capital One Slingshot
Collibra
DQOps
Data Commerce Cloud
Google Cloud BigQuery
Microsoft Power BI
NLP Lab
New Relic
Protegrity
Sifflet
Syntho
Tabular
Zing Data

Integrations

Openbridge
definity
AnalyticsCreator
Ango Hub
Ascend
Azure Data Lake
Capital One Slingshot
Collibra
DQOps
Data Commerce Cloud
Google Cloud BigQuery
Microsoft Power BI
NLP Lab
New Relic
Protegrity
Sifflet
Syntho
Tabular
Zing Data

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

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

Product Features

Big Data

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

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Alternatives

Alternatives

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