Databricks logo

Databricks

0(0 reviews)
Software Status:Active

About Databricks

Databricks is a unified platform for data, analytics, and AI from Databricks that supports a data-centric approach to building AI. It provides features such as Lakehouse Architecture, Mosaic Research, and tools for Executives and Startups, helping organizations use their data effectively. Databricks simplifies ETL processes and data warehousing, allowing businesses to integrate various data sources efficiently and gain actionable insights. The platform aims to assist industry leaders in improving their data and AI strategies. Key capabilities: Lakehouse Architecture Mosaic Research tools for Executives tools for Startups data integration Best for: organizations that need a comprehensive solution for data management and AI development.

Databricks Details

Vendor
Databricks
Year Launched
2013
Location
160 Spear St, San Francisco, CA 94105
Deployment
cloud
Training Options
documentation, videos
Countries Served
All Countries
Languages
English
Users
Data Analysts, Data Engineers, Data Scientists, Data Architects, Business Analysts, Data Managers, IT Professionals
Industries Served
Communications, Financial Services, Healthcare and Life Sciences, Manufacturing, Media and Entertainment, Public Sector, Retail
Tags
Apache Spark, Apache Spark Training, Cloud Computing, Big Data, Data Science, Delta Lake, Data Lakehouse, MLflow, Machine Learning, Data Engineering, Data Warehousing, Data Streaming, Open Source, Generative AI, Artificial Intelligence, Data Intelligence, Data Management, Data Goverance, Generative AI, and AI/ML Ops

Databricks's In-App Market Place

Does Databricks have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

0

Mini Apps

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), AUD (A$), CAD (C$), JPY (¥), CNY (¥), INR (₹), RUB (₽), BRL (R$), KRW (₩), MXN (Mex$), SGD (S$), ZAR (R)

Pros & Cons

  • 1. Scalability: Databricks allows users to process and analyze large-scale data efficiently using Apache Spark's distributed computing framework.
  • 2. Unified Platform: Combines data engineering, data science, and machine learning on a single platform, simplifying workflows.
  • 3. Real-Time Analytics: Supports real-time data streaming and batch processing, making it versatile for various use cases.
  • 4. Collaboration: Enables data teams to collaborate in real time through shared notebooks and interactive dashboards.
  • 5. Delta Lake: Offers a reliable, transactionally consistent layer on top of data lakes, supporting ACID transactions.
  • 6. Cloud-Native: Fully integrates with major cloud providers, offering scalability and on-demand resources.
  • 1. Complexity: Databricks can have a steep learning curve, particularly for users new to Apache Spark or distributed computing.
  • 2. Requires Cloud Expertise: While cloud-native, users may need expertise in cloud management for optimal resource allocation and deployment.
  • 3. Limited Support for Non-Technical Users: Some features may be challenging for non-technical users without data science or engineering expertise

Databricks's Support Options

Databricks's Alternatives