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Databricks VS Google Cloud Monitoring

Compare Databricks VS Google Cloud Monitoring and see what are their differences

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Contents:
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  3. » Reviews
  4. » Alternatives

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Google Cloud Monitoring logo Google Cloud Monitoring

Gain visibility into the performance, uptime, and overall health of cloud-powered apps on Google Cloud and other cloud or on-premises environments.
  • Databricks Landing page
    Landing page //
    2023-09-14
  • Google Cloud Monitoring Landing page
    Landing page //
    2023-08-01

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.

Google Cloud Monitoring features and specs

  • Integration with Google Cloud Platform
    Google Cloud Monitoring offers seamless integration with other Google Cloud services, allowing for unified monitoring and easy setup for users already using Google Cloud products.
  • Comprehensive Metrics and Alerts
    It provides a wide range of metrics and customizable alerts, enabling users to closely monitor their applications and systems for any issues and take proactive measures.
  • Custom Dashboards
    Users can create custom dashboards to visualize important metrics in a way that makes sense for their specific needs, enhancing the ability to quickly spot trends and anomalies.
  • Scalability
    The platform is designed to scale easily, handling the needs of both small applications and large, complex systems without a loss in performance or manageability.
  • Built-In Logging and Tracing
    Google Cloud Monitoring integrates with Google Cloud Logging and Cloud Trace, providing deeper insights by correlating logs and traces with metrics.

Possible disadvantages of Google Cloud Monitoring

  • Complexity for New Users
    For users who are not already familiar with Google Cloud Platform, the initial learning curve can be quite steep due to the vast array of features and settings.
  • Cost
    While there is a free tier, the pricing can become expensive as usage grows, especially for larger deployments that require advanced features and more data processed.
  • Limited Third-Party Integrations
    Compared to some dedicated monitoring solutions, Google Cloud Monitoring may have fewer integrations with third-party services and tools, which can be a limitation for some users.
  • Regional Availability
    Some features may have limited availability depending on the region, which could affect users operating in locations where certain services are not fully supported.
  • Potential for Information Overload
    Due to the comprehensive range of metrics and notifications, users may find themselves overwhelmed with information if dashboards and alerts are not carefully configured.

Databricks videos

+ Add

Introduction to Databricks

More videos:

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

Google Cloud Monitoring videos

+ Add

Cloud Monitoring in a minute

More videos:

  • Tutorial - How to Get Started with Google Cloud Monitoring

Category Popularity

0-100% (relative to Databricks and Google Cloud Monitoring)

Databricks

Google Cloud Monitoring

Data Dashboard
100 100%
Data Dashboard
0% 0
Dev Ops
0 0%
Dev Ops
100% 100
Big Data Analytics
100 100%
Big Data Analytics
0% 0
Monitoring Tools
0 0%
Monitoring Tools
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 Databricks and Google Cloud Monitoring

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

Google Cloud Monitoring Reviews

We have no reviews of Google Cloud Monitoring yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Databricks should be more popular than Google Cloud Monitoring. It has been mentiond 18 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.

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
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Google Cloud Monitoring mentions (7)

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What are some alternatives?

When comparing Databricks and Google Cloud Monitoring, you can also consider the following products

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

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

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.

Cortex Project - Horizontally scalable, highly available, multi-tenant, long term Prometheus.

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.

Google Cloud Functions - A serverless platform for building event-based microservices.

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