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Azure Databricks VS Amazon CloudWatch

Compare Azure Databricks VS Amazon CloudWatch and see what are their differences

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Azure Databricks logo Azure Databricks

Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

Amazon CloudWatch logo Amazon CloudWatch

Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS.
  • Azure Databricks Landing page
    Landing page //
    2023-04-02
  • Amazon CloudWatch Landing page
    Landing page //
    2023-03-26

Azure Databricks features and specs

  • Scalability
    Azure Databricks enables easy scaling of workloads up or down, allowing users to handle large volumes of data and perform distributed processing efficiently.
  • Integration
    Seamlessly integrates with other Azure services, such as Azure Data Lake Storage and Azure SQL Data Warehouse, facilitating a streamlined data pipeline.
  • Collaboration
    Offers collaborative features like notebooks that allow multiple users to work together easily on data analytics projects.
  • Performance Optimization
    Built on top of Apache Spark, Azure Databricks provides high performance and optimized execution for data engineering and machine learning tasks.
  • Managed Service
    As a fully managed service, it handles infrastructure provisioning and maintenance, enabling users to focus on data insights rather than backend management.

Possible disadvantages of Azure Databricks

  • Cost
    Azure Databricks can be expensive, particularly for large-scale and long-running workloads, which may be a concern for budget-conscious organizations.
  • Complexity
    Despite its capabilities, Azure Databricks may have a steep learning curve, especially for users not familiar with Apache Spark.
  • Vendor Lock-in
    Leveraging Azure-specific services can lead to vendor lock-in, making it challenging to migrate workloads and data to other cloud platforms.
  • Limited Offline Capabilities
    As a cloud-native service, it requires an active internet connection and might not suit scenarios that require offline processing.
  • Compliance Concerns
    Due to Azure Databricks' integration with Azure, users need to carefully manage compliance and data governance, which might be complex in multi-regional deployments.

Amazon CloudWatch features and specs

  • Comprehensive Monitoring
    Amazon CloudWatch offers extensive monitoring capabilities for AWS resources, applications, and services, providing real-time insights into system performance and operational health.
  • Scalability
    CloudWatch can handle monitoring data for resources at any scale, from small test environments to large-scale production deployments, easily scaling with your AWS infrastructure.
  • Seamless AWS Integration
    As a native AWS service, CloudWatch integrates seamlessly with other AWS services like EC2, RDS, S3, and Lambda, simplifying the process of setting up and managing monitoring.
  • Custom Metrics
    Users can publish their own custom metrics, allowing them to monitor specific data points relevant to their use case, in addition to the default metrics provided by AWS services.
  • Automated Actions
    With CloudWatch Alarms, users can set predefined thresholds to trigger automated actions such as sending notifications, executing Lambda functions, or altering auto-scaling groups.

Possible disadvantages of Amazon CloudWatch

  • Cost
    Depending on usage, monitoring a large number of resources or high-resolution custom metrics can become costly, potentially impacting overall cloud expenditure.
  • Complexity
    Although CloudWatch is powerful, it can be complex to set up and manage, particularly for users not familiar with AWS terminology and monitoring concepts.
  • Limited Third-Party Integration
    While CloudWatch integrates well with AWS services, integration with third-party tools is not as seamless. This might require additional configuration or third-party solutions for comprehensive monitoring.
  • Lag in Metric Visibility
    There can be a slight delay in the visibility of data points, especially for high-resolution metrics, which may delay immediate troubleshooting and resolution.
  • Basic Dashboarding
    The default dashboards provided by CloudWatch can be quite basic and may not meet the advanced visualization needs of some users, requiring additional tools for creating more sophisticated dashboards.

Azure Databricks videos

Azure Databricks is Easier Than You Think

More videos:

  • Review - Ingest, prepare & transform using Azure Databricks & Data Factory | Azure Friday
  • Review - Azure Databricks - What's new! | DB102

Amazon CloudWatch videos

No Amazon CloudWatch videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Azure Databricks and Amazon CloudWatch)
Technical Computing
100 100%
0% 0
Monitoring Tools
0 0%
100% 100
Office & Productivity
100 100%
0% 0
Log Management
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Azure Databricks and Amazon CloudWatch

Azure Databricks Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Azure Databricks is a data analytics tool optimized for Microsoft’s Azure cloud services solution. It provides three development environments for data-intensive apps, namely Databricks SQL, Databricks Machine Learning, and Databricks Data Science & Engineering.The platform supports languages including Python, Java, R, Scala, and SQL, plus data science frameworks and...
Source: theqalead.com

Amazon CloudWatch Reviews

35+ Of The Best CI/CD Tools: Organized By Category
Amazon CloudWatch is a detection solution for AWS cloud applications and other resources. For instance, you can use it to monitor Amazon services such as EC2. It will automatically alert and inform you of any anomalies it detects. Additionally, Amazon CloudWatch gives you the ability to track and collect metrics.
PagerDuty Alternatives
Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS.
Source: zapier.com

Social recommendations and mentions

Based on our record, Amazon CloudWatch seems to be a lot more popular than Azure Databricks. While we know about 71 links to Amazon CloudWatch, we've tracked only 2 mentions of Azure Databricks. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Azure Databricks mentions (2)

  • Top 30 Microsoft Azure Services
    In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 4 years ago
  • ZooKeeper-free Kafka is out. First Demo
    https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 4 years ago

Amazon CloudWatch mentions (71)

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What are some alternatives?

When comparing Azure Databricks and Amazon CloudWatch, you can also consider the following products

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.

AWS Budgets - Cloud Cost Management

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

AWS Cost Explorer - Cloud Cost Management

MicroStrategy - MicroStrategy is a cloud-based platform providing business intelligence, mobile intelligence and network applications.

NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.