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Amazon CloudWatch VS Databricks

Compare Amazon CloudWatch VS Databricks and see what are their differences

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Amazon CloudWatch logo Amazon CloudWatch

Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS.

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?
  • Amazon CloudWatch Landing page
    Landing page //
    2023-03-26
  • Databricks Landing page
    Landing page //
    2023-09-14

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.

Databricks features and specs

  • Unified Data Analytics Platform
    Databricks integrates various data processing and analytics tools, offering a unified environment for data engineering, machine learning, and business analytics. This integration can streamline workflows and reduce the complexity of data management.
  • Scalability
    Databricks leverages Apache Spark and other scalable technologies to handle large datasets and high computational workloads efficiently. This makes it suitable for enterprises with significant data processing needs.
  • Collaborative Environment
    The platform offers collaborative notebooks that allow data scientists, engineers, and analysts to work together in real-time. This enhances productivity and fosters better communication within teams.
  • Performance Optimization
    Databricks includes various performance optimization features such as caching, indexing, and query optimization, which can significantly speed up data processing tasks.
  • Support for Various Data Formats
    The platform supports a wide range of data formats and sources, including structured, semi-structured, and unstructured data, making it versatile and adaptable to different use cases.
  • Integration with Cloud Providers
    Databricks is designed to work seamlessly with major cloud providers like AWS, Azure, and Google Cloud, allowing users to easily integrate it into their existing cloud infrastructure.

Possible disadvantages of Databricks

  • Cost
    Databricks can be expensive, especially for large-scale deployments or high-frequency usage. It may not be the most cost-effective solution for smaller organizations or projects with limited budgets.
  • Complexity
    While powerful, Databricks can be complex to set up and manage, requiring specialized knowledge in Apache Spark and cloud infrastructure. This might lead to a steeper learning curve for new users.
  • Dependency on Cloud Providers
    Being heavily integrated with cloud providers, Databricks might face issues like vendor lock-in, where switching providers becomes difficult or costly.
  • Limited Offline Capabilities
    Databricks is primarily designed for cloud environments, which means offline or on-premise capabilities are limited, posing challenges for organizations with strict data governance policies.
  • Resource Management
    Efficiently managing and allocating resources can be challenging in Databricks, especially in large multi-user environments. Mismanagement of resources could lead to increased costs and reduced performance.

Analysis of Amazon CloudWatch

Overall verdict

  • Amazon CloudWatch is generally considered good due to its versatility, scalability, and deep integration with AWS services. Its ability to deliver insights and analytics makes it essential for businesses to ensure the reliability and efficiency of their cloud operations.

Why this product is good

  • Amazon CloudWatch is a robust monitoring and management service provided by AWS. It allows you to collect and analyze operational data from various AWS resources and applications to provide high granularity of performance metrics. This service enables real-time monitoring, automated actions, and flexible dashboard configurations. The integration with AWS services and the ability to set alarms and automate responses make it invaluable for maintaining the health and performance of applications on AWS.

Recommended for

  • Organizations using AWS services looking for native monitoring solutions.
  • DevOps teams needing detailed metric collection and analysis.
  • Businesses that require custom dashboards for real-time data visualization.
  • Teams aiming to automate responses based on predefined performance thresholds.

Amazon CloudWatch videos

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Databricks videos

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Introduction to Databricks

More videos:

  • Tutorial - Azure Databricks Tutorial | Data transformations at scale
  • Review - Databricks - Data Movement and Query

Category Popularity

0-100% (relative to Amazon CloudWatch and Databricks)

Amazon CloudWatch

Databricks

Monitoring Tools
100 100%
Monitoring Tools
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Log Management
100 100%
Log Management
0% 0
Big Data Analytics
0 0%
Big Data Analytics
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 Amazon CloudWatch and Databricks

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.
Source: www.cloudzero.com
PagerDuty Alternatives
Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS.
Source: zapier.com

Databricks Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Databricks notebooks are a popular tool for developing code and presenting findings in data science and machine learning. Databricks Notebooks support real-time multilingual coauthoring, automatic versioning, and built-in data visualizations.
Source: lakefs.io
7 best Colab alternatives in 2023
Databricks is a platform built around Apache Spark, an open-source, distributed computing system. The Databricks Community Edition offers a collaborative workspace where users can create Jupyter notebooks. Although it doesn't offer free GPU resources, it's an excellent tool for distributed data processing and big data analytics.
Source: deepnote.com
Top 5 Cloud Data Warehouses in 2023
Jan 11, 2023 The 5 best cloud data warehouse solutions in 2023Google BigQuerySource: https://cloud.google.com/bigqueryBest for:Top features:Pros:Cons:Pricing:SnowflakeBest for:Top features:Pros:Cons:Pricing:Amazon RedshiftSource: https://aws.amazon.com/redshift/Best for:Top features:Pros:Cons:Pricing:FireboltSource: https://www.firebolt.io/Best for:Top...
Source: www.shipyardapp.com
Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
Databricks is a simple, fast, and collaborative analytics platform based on Apache Spark with ETL capabilities. It accelerates innovation by bringing together data science and data science businesses. It is a fully managed open-source version of Apache Spark analytics with optimized connectors to storage platforms for the fastest data access.
Source: visual-flow.com
Top Big Data Tools For 2021
Now Azure Databricks achieves 50 times better performance thanks to a highly optimized version of Spark. Databricks also enables real-time co-authoring and automates versioning. Besides, it features runtimes optimized for machine learning that include many popular libraries, such as PyTorch, TensorFlow, Keras, etc.
Source: blog.bismart.com

Social recommendations and mentions

Based on our record, Amazon CloudWatch should be more popular than Databricks. It has been mentiond 74 times since March 2021. 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.

Amazon CloudWatch mentions (74)

View more

Databricks mentions (18)

  • Platform Engineering Abstraction: How to Scale IaC for Enterprise
    Vendors like Confluent, Snowflake, Databricks, and dbt are improving the developer experience with more automation and integrations, but they often operate independently. This fragmentation makes standardizing multi-directional integrations across identity and access management, data governance, security, and cost control even more challenging. Developing a standardized, secure, and scalable solution for... - Source: dev.to / about 1 year ago
  • dolly-v2-12b
    Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA). Source: over 2 years ago
  • Clickstream data analysis with Databricks and Redpanda
    Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose. - Source: dev.to / about 3 years ago
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake. - Source: dev.to / over 3 years ago
  • A Quick Start to Databricks on AWS
    Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward. - Source: dev.to / over 3 years ago
View more

What are some alternatives?

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

AWS Budgets - Cloud Cost Management

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

AWS Cost Explorer - Cloud Cost Management

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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