Databricks vs Google Analytics

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Databricks

476
724
+ 1
8
Google Analytics

125.9K
48.2K
+ 1
5K
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Databricks vs Google Analytics: What are the differences?

### Key Differences between Databricks and Google Analytics

1. **Use Case**: Databricks is primarily a data engineering and data science platform that focuses on scalable data processing, while Google Analytics is a web analytics service that tracks and reports website traffic. Databricks is used for data processing, advanced analytics, and machine learning tasks, while Google Analytics is used for tracking user behavior on websites.

2. **Deployment**: Databricks is typically deployed on cloud platforms like AWS or Azure, providing a unified analytics platform for data engineering, data science, and business intelligence. On the other hand, Google Analytics is a web-based service that relies on placing tracking codes on website pages to collect and analyze data.

3. **Data Sources**: Databricks can connect to a wide variety of data sources including databases, data lakes, and streaming platforms to perform advanced analytics and machine learning tasks. In contrast, Google Analytics mainly relies on web data generated by website visitors to provide insights on user behavior and website performance.

4. **Customization**: Databricks offers extensive customization options for data processing pipelines, machine learning models, and analytics workflows, allowing users to tailor their data workflows according to specific requirements. Google Analytics, while offering some customization features, is primarily focused on providing standardized reports and metrics for website analytics.

5. **Collaboration**: Databricks provides collaborative features that allow multiple users to work on the same projects simultaneously, share code, and collaborate on data analysis tasks. Google Analytics, on the other hand, is more focused on individual users accessing analytics reports and insights for website optimization.

6. **Scalability**: Databricks is designed to handle large-scale data processing tasks and machine learning models, making it suitable for processing massive datasets and running complex analytics workflows. Google Analytics is more suited for small to medium-sized websites and may face limitations when dealing with extremely large amounts of data.

In Summary, Databricks is a scalable data engineering and data science platform deployed on cloud services, while Google Analytics is a web-based service focused on tracking website traffic and user behavior.
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Pros of Databricks
Pros of Google Analytics
  • 1
    Best Performances on large datasets
  • 1
    True lakehouse architecture
  • 1
    Scalability
  • 1
    Databricks doesn't get access to your data
  • 1
    Usage Based Billing
  • 1
    Security
  • 1
    Data stays in your cloud account
  • 1
    Multicloud
  • 1.5K
    Free
  • 926
    Easy setup
  • 890
    Data visualization
  • 698
    Real-time stats
  • 405
    Comprehensive feature set
  • 181
    Goals tracking
  • 154
    Powerful funnel conversion reporting
  • 138
    Customizable reports
  • 83
    Custom events try
  • 53
    Elastic api
  • 14
    Updated regulary
  • 8
    Interactive Documentation
  • 3
    Google play
  • 2
    Industry Standard
  • 2
    Walkman music video playlist
  • 2
    Advanced ecommerce
  • 1
    Medium / Channel data split
  • 1
    Easy to integrate
  • 1
    Financial Management Challenges -2015h
  • 1
    Lifesaver
  • 1
    Irina

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Cons of Databricks
Cons of Google Analytics
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    • 11
      Confusing UX/UI
    • 8
      Super complex
    • 6
      Very hard to build out funnels
    • 4
      Poor web performance metrics
    • 3
      Very easy to confuse the user of the analytics
    • 2
      Time spent on page isn't accurate out of the box

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    What is Databricks?

    Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.

    What is Google Analytics?

    Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications.

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    What tools integrate with Databricks?
    What tools integrate with Google Analytics?

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    Blog Posts

    Jul 2 2019 at 9:34PM

    Segment

    Google AnalyticsAmazon S3New Relic+25
    10
    6736
    GitHubPythonNode.js+47
    54
    72281
    GitHubGitSlack+30
    27
    18275
    JavaScriptGitHubGit+33
    20
    2080
    JavaScriptGitHubPython+42
    53
    21803
    What are some alternatives to Databricks and Google Analytics?
    Snowflake
    Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
    Azure Databricks
    Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
    Domino
    Use our cloud-hosted infrastructure to securely run your code on powerful hardware with a single command — without any changes to your code. If you have your own infrastructure, our Enterprise offering provides powerful, easy-to-use cluster management functionality behind your firewall.
    Confluent
    It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    See all alternatives