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Databricks VS SuperOps

Compare Databricks VS SuperOps and see what are their differences

NinjaOne
NinjaOne (Formerly NinjaRMM) provides remote monitoring and management software that combines powerful functionality with a fast, modern UI. Easily remediate IT issues, automate common tasks, and support end-users with powerful IT management tools. featured
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  2. » Videos
  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?

SuperOps logo SuperOps

Modern PSA and RMM Software for MSP's and IT Teams
Visit Website
  • Databricks Landing page
    Landing page //
    2023-09-14
  • SuperOps Homescreen
    Homescreen //
    2025-05-13
  • SuperOps Project management
    Project management //
    2025-05-13
  • SuperOps Policy Management
    Policy Management //
    2025-05-13
  • SuperOps patch Management
    patch Management //
    2025-05-13
  • SuperOps Network Monitoring
    Network Monitoring //
    2025-05-13
  • SuperOps Invoicing
    Invoicing //
    2025-05-13
  • SuperOps Event Triggers
    Event Triggers //
    2025-05-13
  • SuperOps Client management
    Client management //
    2025-05-13
  • SuperOps Asset Management
    Asset Management //
    2025-05-13

SuperOps is a future-ready, unified PSA-RMM platform for fast-growing MSPs. Powered with the goodness of AI and intelligent automation, SuperOps.com is packed with all the features that a modern MSP needs, including project management and IT documentation.

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.

SuperOps features and specs

  • User-Friendly Interface
    SuperOps offers an intuitive and easy-to-navigate interface that can be accessed with minimal training, making it user-friendly for IT and service management teams.
  • Comprehensive ITSM Tools
    This platform provides an extensive set of IT Service Management (ITSM) tools, allowing businesses to efficiently handle IT operations and workflows in one unified environment.
  • Automation Capabilities
    SuperOps includes automation features that simplify repetitive tasks, thereby saving time and reducing the potential for human errors in processes.
  • Integration Options
    The platform offers seamless integration with various third-party tools and services, enhancing its functionality and allowing users to have a more cohesive IT ecosystem.
  • Scalability
    SuperOps can scale according to the size of the business, providing flexibility for growth and adjusting resources as necessary.

Databricks videos

+ Add

Introduction to Databricks

More videos:

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

SuperOps videos

+ Add

Introducing SuperOps.ai, the new-age PSA-RMM solution for MSPs

More videos:

  • Review - Automation Overview | SuperOps.ai

Category Popularity

0-100% (relative to Databricks and SuperOps)

Databricks

SuperOps

Data Dashboard
100 100%
Data Dashboard
0% 0
Automation
0 0%
Automation
100% 100
Big Data Analytics
100 100%
Big Data Analytics
0% 0
Workflow Automation
0 0%
Workflow Automation
100% 100

User comments

Share your experience with using Databricks and SuperOps. For example, how are they different and which one is better?
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Reviews

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

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

SuperOps Reviews

We have no reviews of SuperOps yet.
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Social recommendations and mentions

Based on our record, Databricks should be more popular than SuperOps. 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
View more

SuperOps mentions (2)

  • RMM
    Chris from SuperOps.ai here. I would definitely suggest you to have a look at SuperOPs PSA&RMM platform as you are looking an affordable and modern solution to kick start your business. We do also have special offers for the start up. So feel free to take a free demo with us today!. Source: over 3 years ago
  • Looking for something to pair with Connectwise Control (Screen connect)
    Bluetrait.io might be something to look into (Free for the first 50 endpoints as well). I had it set up for Screen Connect integration as an initial agent task after first install. superops.ai also has Screen Connect integration. Source: almost 4 years ago

What are some alternatives?

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

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

Atera - Atera is reinventing the world of IT by harnessing AI to power our all-in-one Remote Monitoring and Management (RMM), Helpdesk, Ticketing, and automations platform—streamlining organizational IT management at scale with our proprietary Action AI™.

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.

NinjaOne - NinjaOne (Formerly NinjaRMM) provides remote monitoring and management software that combines powerful functionality with a fast, modern UI. Easily remediate IT issues, automate common tasks, and support end-users with powerful IT management tools.

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.

Zapier - Connect the apps you use everyday to automate your work and be more productive. 1000+ apps and easy integrations - get started in minutes.

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