Databricks vs Google Analytics

Need advice about which tool to choose?Ask the StackShare community!

Databricks

248
411
+ 1
8
Google Analytics

108.6K
33.4K
+ 1
5K
Add tool

Databricks vs Google Analytics: What are the differences?

Developers describe Databricks as "A unified analytics platform, powered by Apache Spark". 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. On the other hand, Google Analytics is detailed as "Enterprise-class web analytics". Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications.

Databricks and Google Analytics can be categorized as "General Analytics" tools.

Some of the features offered by Databricks are:

  • Built on Apache Spark and optimized for performance
  • Reliable and Performant Data Lakes
  • Interactive Data Science and Collaboration

On the other hand, Google Analytics provides the following key features:

  • Analysis Tools- Google Analytics is built on a powerful, easy to use, reporting platform, so you can decide what data you want to view and customize your reports, with just a few clicks.
  • Content Analytics- Content reports help you understand which parts of your website are performing well, which pages are most popular so you can create a better experience for your customers.
  • Social Analytics- The web is a social place and Google Analytics measures success of your social media programs. You can analyze how visitors interact with sharing features on your site (like the Google +1 button) and engage with your content across social platforms.

Airbnb, Uber Technologies, and Spotify are some of the popular companies that use Google Analytics, whereas Databricks is used by Auto Trader, Snowplow Analytics, and Fairygodboss. Google Analytics has a broader approval, being mentioned in 18000 company stacks & 10534 developers stacks; compared to Databricks, which is listed in 7 company stacks and 4 developer stacks.

Get Advice from developers at your company using Private StackShare. Sign up for Private StackShare.
Learn More
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
  • 925
    Easy setup
  • 886
    Data visualization
  • 696
    Real-time stats
  • 403
    Comprehensive feature set
  • 180
    Goals tracking
  • 153
    Powerful funnel conversion reporting
  • 136
    Customizable reports
  • 83
    Custom events try
  • 53
    Elastic api
  • 13
    Updated regulary
  • 8
    Interactive Documentation
  • 3
    Google play
  • 2
    Advanced ecommerce
  • 2
    Walkman music video playlist
  • 1
    Medium / Channel data split
  • 1
    Easy to integrate
  • 1
    Financial Management Challenges -2015h
  • 1
    Lifesaver
  • 1
    Industry Standard

Sign up to add or upvote prosMake informed product decisions

Cons of Databricks
Cons of Google Analytics
    Be the first to leave a con
    • 7
      Confusing UX/UI
    • 5
      Super complex
    • 3
      Very hard to build out funnels
    • 2
      Poor web performance metrics
    • 1
      Time spent on page isn't accurate out of the box
    • 1
      Very easy to confuse the user of the analytics

    Sign up to add or upvote consMake informed product decisions

    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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Databricks?
    What companies use Google Analytics?
    See which teams inside your own company are using Databricks or Google Analytics.
    Sign up for Private StackShareLearn More

    Sign up to get full access to all the companiesMake informed product decisions

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

    Sign up to get full access to all the tool integrationsMake informed product decisions

    Blog Posts

    Jul 2 2019 at 9:34PM

    Segment

    +25
    10
    5595
    +47
    46
    68737
    +30
    25
    15004
    +33
    20
    1638
    +42
    52
    19653
    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