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Databricks vs Maze

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Databricks
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726
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Maze
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Databricks vs Maze: What are the differences?

What is Databricks? 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.

What is Maze? Beautiful & actionable analytics for InVision prototypes. Create missions testers will perform on your InVision’s prototype and discover how your product’s design can be improved, with 0 lines of code.

Databricks and Maze belong to "General Analytics" category of the tech stack.

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, Maze provides the following key features:

  • InVision Analytics
  • Prototype testing
  • Clicks Heatmap

i-surance, Specify, and Fuchsia are some of the popular companies that use Maze, whereas Databricks is used by Auto Trader, Snowplow Analytics, and Fairygodboss. Maze has a broader approval, being mentioned in 3 company stacks & 8 developers stacks; compared to Databricks, which is listed in 7 company stacks and 4 developer stacks.

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Pros of Databricks
Pros of Maze
  • 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
  • 3
    Makes validating protos easier
  • 2
    Easy export and setup

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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 Maze?

Maze empowers product and marketing teams to test anything from prototypes to copy, or round up user feedback—all in one place. Rapidly collect user insights across teams and create better user experiences, together.

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Jobs that mention Databricks and Maze as a desired skillset
Staff Software Engineer
Pinterest
Toronto, ON, CA
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DreamAT InternetUbuntu+5
What companies use Databricks?
What companies use Maze?
See which teams inside your own company are using Databricks or Maze.
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What tools integrate with Databricks?
What tools integrate with Maze?

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What are some alternatives to Databricks and Maze?
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

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