Domo and Splunk Enterprise Platform compete in the data analytics and monitoring category. Domo has an advantage for its ease of use and accessibility for non-technical users.
Features: Domo offers user-friendly data visualization, adaptability for non-technical users, and collaborative tools that enhance process efficiency. Splunk Enterprise Platform provides comprehensive data analysis, real-time monitoring, and customizable dashboards.
Room for Improvement: Domo can be expensive, limiting accessibility for smaller companies, and lacks some advanced analytical capabilities. Splunk Enterprise Platform’s cost structure can be prohibitive without a large data volume, and it may require better training resources for new users.
Ease of Deployment and Customer Service: Domo is noted for its simplicity in deployment, making it accessible for larger rollouts with varied user skill levels. Splunk Enterprise Platform offers robust features but can be complex to configure, requiring strong customer support.
Pricing and ROI: Domo, though pricey, provides significant ROI with its ability to streamline processes, often justifying costs for larger enterprises. Splunk Enterprise Platform is considered expensive, especially for smaller businesses, with ROI heavily dependent on scale and effective data utilization strategy.
If you're actually using Domo at a very limited case and you're being charged $20,000, we've seen ROI there, but once it goes really high, you really need to check your metrics and check your profit.
Splunk Enterprise Platform saves approximately 20 to 30 percent of my time without having to perform different actions separately.
They were quite professional and in around three to five working days, they had identified where they suspected there was an issue and I was able to fix it.
It's very easy to get technical support from Domo.
Support-wise, they are good.
It is crucial for anyone looking to deploy Splunk Enterprise Platform to first certify for their courses, such as the Splunk Administrator and the Power User Administrator certifications, which address all troubleshooting queries.
The fact that you're able to easily identify the pipelines or flows that have errors, and it notifies you when you're building a pipeline where you can run previews and tell where to fix issues, is helpful.
When fetching files larger than 100 MB from SFTP or any other portal, Domo becomes slow due to the heavy file size.
Sigma, which is written for Snowflake, scales more easily than Domo.
Some products can automatically scale, but Splunk requires manual configuration changes to achieve scale, which is slightly outdated compared to modern technologies.
If the server is down, I can upgrade the server resources or create a new node for performance optimization.
Splunk Enterprise Platform is scalable to some extent, which is acceptable.
In recent years, I haven't had such cases. It's quite stable and I don't have any reservations on its stability.
In terms of overall stability of the platform, it's very stable.
During that time, we faced issues from the project side as Domo was not visible in our portal.
It requires managing configuration files and processing operations manually, limiting its auto-scaling capabilities.
Splunk Enterprise Platform is stable when not integrating or adding new devices continuously.
End users require a license to run their own reports and dashboards, which are fairly expensive.
Some technical aspects such as Beast Mode calculation could be improved in Domo, as it would provide more clarity and help in giving insights to clients or customer business team requirements.
One of the areas where we've had frustrations with Domo is the aesthetics. The aesthetics are quite limited compared to other BI tools such as Tableau and Power BI.
The deep learning capabilities need enhancing, especially on Splunk Cloud, where customers find it challenging to use deep learning tools without setting up backend computing resources.
It is complex for inexperienced cybersecurity engineers and requires experienced personnel to handle it effectively.
The cost is the most significant area for improvement in Splunk Enterprise Platform, as it is quite expensive, causing many clients to differ due to this reason.
Domo's pricing is high compared to other BI tools, and it is costly.
For long-time users, it can become expensive, but the trade-off is access to the entire platform instead of licensing different components separately.
They quoted approximately one dollar per KB.
The pricing model is based on ingesting data sizes, not user count, and includes a free tier for up to 500 MB of daily data.
Splunk Enterprise Platform is expensive.
App Studio is valuable because it allows all the customization we needed; we can decode it, with the view and grid which are all I need, drill-downs, and everything can be done the way I need it.
I have been using it for four years and have been able to extract the information I need from it.
The most valuable feature of Domo is the fact that you can connect multiple inputs and you don't have to have a data warehouse.
Splunk Enterprise Platform also has its own Phantom as a SOAR, which is much more refined and gives more accurate results than any other AI integrated SIM tool.
The features that have proven most effective for real-time data analysis include parts of the platform and its automation capabilities.
One valuable feature of Splunk Enterprise Platform is citizen programming, which allows users to manage and compute huge stream-based datasets easily using SPL language.
Product | Market Share (%) |
---|---|
Splunk Enterprise Platform | 1.6% |
Domo | 7.9% |
Other | 90.5% |
Company Size | Count |
---|---|
Small Business | 16 |
Midsize Enterprise | 11 |
Large Enterprise | 20 |
Company Size | Count |
---|---|
Small Business | 11 |
Midsize Enterprise | 1 |
Large Enterprise | 23 |
Domo is a cloud-based, mobile-first BI platform that helps companies drive more value from their data by helping organizations better integrate, interpret and use data to drive timely decision making and action across the business. The Domo platform enhances existing data warehouse and BI tools and allows users to build custom apps, automate data pipelines, and make data science accessible for anyone through automated insights that can be shared with internal or external stakeholders.
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