Jupyter Notebook vs. Splunk Cloud Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Jupyter Notebook
Score 8.5 out of 10
N/A
Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
Splunk Cloud Platform
Score 7.9 out of 10
N/A
Splunk Cloud Platform is a data platform service thats help users search, analyze, visualize and act on data. The service can go live in as little as two days, and with an IT backend managed by Splunk experts.N/A
Pricing
Jupyter NotebookSplunk Cloud Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Jupyter NotebookSplunk Cloud Platform
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Jupyter NotebookSplunk Cloud Platform
Features
Jupyter NotebookSplunk Cloud Platform
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
9.0
22 Ratings
8% above category average
Splunk Cloud Platform
-
Ratings
Connect to Multiple Data Sources10.022 Ratings00 Ratings
Extend Existing Data Sources10.021 Ratings00 Ratings
Automatic Data Format Detection8.514 Ratings00 Ratings
MDM Integration7.415 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
7.0
22 Ratings
19% below category average
Splunk Cloud Platform
-
Ratings
Visualization6.022 Ratings00 Ratings
Interactive Data Analysis8.022 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
9.5
22 Ratings
15% above category average
Splunk Cloud Platform
-
Ratings
Interactive Data Cleaning and Enrichment10.021 Ratings00 Ratings
Data Transformations10.022 Ratings00 Ratings
Data Encryption8.514 Ratings00 Ratings
Built-in Processors9.314 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
9.3
22 Ratings
10% above category average
Splunk Cloud Platform
-
Ratings
Multiple Model Development Languages and Tools10.021 Ratings00 Ratings
Automated Machine Learning9.218 Ratings00 Ratings
Single platform for multiple model development10.022 Ratings00 Ratings
Self-Service Model Delivery8.020 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Jupyter Notebook
10.0
20 Ratings
16% above category average
Splunk Cloud Platform
-
Ratings
Flexible Model Publishing Options10.020 Ratings00 Ratings
Security, Governance, and Cost Controls10.019 Ratings00 Ratings
Security Information and Event Management (SIEM)
Comparison of Security Information and Event Management (SIEM) features of Product A and Product B
Jupyter Notebook
-
Ratings
Splunk Cloud Platform
8.2
20 Ratings
4% above category average
Centralized event and log data collection00 Ratings9.019 Ratings
Correlation00 Ratings8.419 Ratings
Event and log normalization/management00 Ratings9.220 Ratings
Deployment flexibility00 Ratings7.320 Ratings
Integration with Identity and Access Management Tools00 Ratings7.818 Ratings
Custom dashboards and workspaces00 Ratings9.020 Ratings
Host and network-based intrusion detection00 Ratings8.217 Ratings
Data integration/API management00 Ratings7.510 Ratings
Behavioral analytics and baselining00 Ratings7.28 Ratings
Rules-based and algorithmic detection thresholds00 Ratings8.210 Ratings
Response orchestration and automation00 Ratings7.58 Ratings
Reporting and compliance management00 Ratings8.810 Ratings
Incident indexing/searching00 Ratings8.811 Ratings
Best Alternatives
Jupyter NotebookSplunk Cloud Platform
Small Businesses
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Score 10.0 out of 10
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Score 7.6 out of 10
Medium-sized Companies
Posit
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Score 10.0 out of 10
Sumo Logic
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Score 8.8 out of 10
Enterprises
Posit
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Score 10.0 out of 10
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Score 8.8 out of 10
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User Ratings
Jupyter NotebookSplunk Cloud Platform
Likelihood to Recommend
10.0
(23 ratings)
9.2
(18 ratings)
Likelihood to Renew
-
(0 ratings)
9.1
(1 ratings)
Usability
10.0
(2 ratings)
9.0
(5 ratings)
Support Rating
9.0
(1 ratings)
7.2
(4 ratings)
User Testimonials
Jupyter NotebookSplunk Cloud Platform
Likelihood to Recommend
Open Source
I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
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Cisco
Splunk is excellent when all your data is in one location. Its ability to correlate all that data is intuitive (once the hurdle of learning the query language is overcome). It is also easy to standardize the presentation of information to the company. When data is siloed/standalone, other systems can be cheaper and faster to implement.
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Pros
Open Source
  • Simple and elegant code writing ability. Easier to understand the code that way.
  • The ability to see the output after each step.
  • The ability to use ton of library functions in Python.
  • Easy-user friendly interface.
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Cisco
  • This SIEM consolidates multiple data points and offers several features and benefits, creating custom dashboards and managing alert workflows.
  • Splunk Cloud provides a simple way to have a central monitoring and security solution. Though it does not have a huge learning curve, you should spend some time learning the basics.
  • Splunk Cloud enables me to create and schedule statistical reports on network use for Management.
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Cons
Open Source
  • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
  • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
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Cisco
  • The SPL programming language that the queries are built in is not very intuitive.
  • There should be a better repository of pre-built queries for what I would think of as common Active Directory usage monitoring.
  • I would like to see more free training/familiarization information made available.
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Likelihood to Renew
Open Source
No answers on this topic
Cisco
Ease of use and have all the features we need
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Usability
Open Source
Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
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Cisco
What it does well:
- Powerful SPL query language for advanced users
- Excellent visualization dashboards
- Comprehensive documentation and community support
Where it needs work:
- Steep learning curve for SPL syntax
- Non-Intuitive UI for beginners
- Complex administration and data model configuration
- Search performance degrades with poor query optimization
Bottom line: Enterprise-grade tool requiring dedicated training investment. Best for teams with experienced analysts.
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Support Rating
Open Source
I haven't had a need to contact support. However, all required help is out there in public forums.
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Cisco
Splunk Cloud support is sorely lacking unfortunately. The portal where you submit tickets is not very good and is lacking polish. Tickets are left for days without any updates and when chased it is only sometimes you get a reply back. I get the feeling the support team are very understaffed and have far too much going on. From what I know, Splunk is aware of this and seem to be trying to remedy it.
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Alternatives Considered
Open Source
With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
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Cisco
Search Processing Language really is a game changer for writing easy-to-understand and maintainable queries on your data base logs. Once understood, setting up and validating a query can be done in no time- which leaves us the option to focus on more monitoring and improved services. We have no other tools that utilizes data this efficiently
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Return on Investment
Open Source
  • Positive impact: flexible implementation on any OS, for many common software languages
  • Positive impact: straightforward duplication for adaptation of workflows for other projects
  • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
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Cisco
  • End-end visibility across your departmental silos
  • Strengthen the overall global monitoring posture
  • Move from Reactive to Proactive Monitoring
  • Highly secure environment at your finger-tips
  • Takes you away from managing infrastructure/administration, allows saving time & money. Reduce the overall TCO (Total Cost of Ownership)
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ScreenShots