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Azure Databricks vs Maze: What are the differences?
What is Azure Databricks? Fast, easy, and collaborative Apache Spark–based analytics service. Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
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.
Azure Databricks and Maze belong to "General Analytics" category of the tech stack.
Some of the features offered by Azure Databricks are:
- Optimized Apache Spark environment
- Autoscale and auto terminate
- Collaborative workspace
On the other hand, Maze provides the following key features:
- InVision Analytics
- Prototype testing
- Clicks Heatmap
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Pros of Maze
Pros of Azure Databricks
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Pros of Maze
- Makes validating protos easier3
- Easy export and setup2
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What is Azure Databricks?
Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
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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What companies use Azure Databricks?
What companies use Maze?
What companies use Azure Databricks?
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What tools integrate with Azure Databricks?
What tools integrate with Maze?
What tools integrate with Azure Databricks?
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What are some alternatives to Azure Databricks and Maze?
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.
Azure Machine Learning
Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.
Azure HDInsight
It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data.
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.
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.