Splunk vs Pentaho

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Our analysts compared Splunk vs Pentaho based on data from our 400+ point analysis of Business Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

Splunk Software Tool
Pentaho Software Tool

Product Basics

Splunk is a leading platform for analyzing machine data. Gathering this data helps your business analysts recommend process improvements to save money and time. More than that, enterprises rely on it to stay on top of cybersecurity, including data breaches.

Collect process data and let your business analysts peek under the hood and identify risks in advance. Besides data ingestion, transformation, analysis and reporting are built in. Dashboards and reports provide interactive views.

It deploys wherever you need it — in the cloud, on-premise or as part of a hybrid setup. Pricing is complex but flexible and includes term and annual subscriptions.

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Pentaho is a data integration and analytics platform that helps businesses extract, transform, analyze, and visualize data from diverse sources. It caters to organizations navigating growing data volumes and seeking insights for informed decision-making. Users praise Pentaho's open-source, free core version, making it a budget-friendly option for beginners or small teams. Its wide range of tools tackles various data challenges, from basic reporting to advanced analytics. Scalability shines for larger datasets, handling complex processing effectively. Additionally, an active community offers valuable support. However, prepare for a steeper learning curve compared to more user-friendly options. Limited documentation can occasionally leave users struggling. Users report encountering bugs and glitches, potentially requiring technical expertise. Be mindful of resource intensiveness, as large-scale operations might demand powerful hardware. While customization options exist, some users crave more flexibility. Overall, Pentaho offers a powerful, free data platform, with trade-offs between its extensive capabilities and ease of use. Consider its strengths and limitations in the context of your specific needs and technical expertise.

Pros
  • Open-source and free
  • Wide range of tools
  • Scalable for large datasets
  • Active community support
  • Integration with various platforms
Cons
  • Steeper learning curve
  • Limited documentation
  • Occasional bugs and glitches
  • Can be resource-intensive
  • Limited customization options
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$150/GB, Monthly
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Tailored to your specific needs
$100 Monthly, Freemium
Get a free price quote
Tailored to your specific needs
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Windows
Mac
Linux
Android
Chromebook
Windows
Mac
Linux
Android
Chromebook
Cloud
On-Premise
Mobile
Cloud
On-Premise
Mobile

Product Assistance

Documentation
In Person
Live Online
Videos
Webinars
Documentation
In Person
Live Online
Videos
Webinars
Email
Phone
Chat
FAQ
Forum
Knowledge Base
24/7 Live Support
Email
Phone
Chat
FAQ
Forum
Knowledge Base
24/7 Live Support

Product Insights

  • Maximize ROI: Design tailored campaigns and realistic budgets. Get a combined view of buyer and usage data from social media, email and web analytics tools, thanks to its data ingestion ability.
  • Predict Sales: Convert more visitors with targeted email campaigns or ads that remind them about specific products they viewed. Predict sales trends accurately by gathering market data from different sources.
  • Delight Customers: Keep buyers happy by solving their issues in the first call using personalized insight and product data, thanks to improved processes.
  • Boost Efficiency: Stop scrambling to fix unplanned downtime. Schedule predictive maintenance with sensor data from machines. It forecasts potential issues before they happen.
  • Support Finance: Combine your on-site and cloud data for a unified view. It acts like a real-time financial dashboard, giving you a clear picture of market activity and automating tasks to manage risk and save time.
  • Scale Seamlessly: Handle enterprise workloads efficiently by scaling vertically and horizontally. It scales by adding nodes, CPUs and data storage to ensure fast results even when dealing with a lot of information.
  • Manage Resources: Identify blockers and gaps in business processes. Monitor system usage with logs and dashboards and get notified when resource consumption exceeds limits.
  • Monitor Performance: Track everything from applications to hardware and get alerts if anything goes wrong. Splunk Observability acts like a watchful eye on system health.
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  • High-Level Overviews: Track KPI progress, capitalize on wins or improve upon stagnant growth. 
  • Enhanced Productivity: A code-free design produces a 15x boost in productivity. Execution of Spark or Hadoop jobs in clusters leads to high-performance output. 
  • Big Data Analytics: Integrate with Hadoop and Spark to ensure big data aggregation, preparation and integration, interactive visualization, analysis, and prediction. Blend multiple sources and process data at scale in a visual design environment. 
  • Efficient Data Management: Improve pipeline management for structured and unstructured data using flow orchestration, managed from a single console. Data engineers and analysts can perform automated data integration tasks for onboarding and data prep using templates.  
  • Predictive Analytics: Monitor, evaluate, compare and rebuild predictive models to perform predictive analysis using machine learning algorithms. Maximize model accuracy while in production and choose from a broad selection of evaluation statistics to identify degraded models. Analyze model performance and uncover inadequacies using rich visualizations. 
  • Community-Driven Tools: Use external components or plugins to extend standard functions. Installed on top of the platform, the plugins aid customizations. 
  • Metadata Editor: Automate data ingestion and onboarding, and cleanse and blend to create analytics-ready data models.  
  • Embedded Analytics: Embed real-time reports and dashboards into existing applications, web-based user interfaces and web APIs. Leverage multiple options to embed the application into clients’ systems. Supports multi-tenant deployment with single sign-on and security integration. 
  • Multi-Cloud Support: Deploy in a multi, hybrid or private cloud environment, with a single tool to simplify architecture management. Ensures connectivity to cloud storage and computing in AWS, Google Cloud and Microsoft Azure. Supports bulk loading of cloud data warehouses, including Amazon Redshift, Snowflake and Google BigQuery. 
  • Streaming Analytics: Get constant statistical analysis from data streams, collected from sources such as log files, social media, IoT platforms, telemetry and more. Manage, monitor and record real-time analytics of live streaming data to quickly extract the necessary information. 
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  • Data Integration: Pull data from on-premise, cloud, streaming sources and machines. Include relational databases using Splunk DB, an add-on module. Splunk doesn’t support SQL databases otherwise.
  • Device Diversity: Gather user and system data from personal and network devices, servers and IoT sensors. Access reports and dashboards on a web interface from iPads, TVs and phones.
  • SPL: Search, filter and analyze data with a powerful query language. Boost adoption with natural language commands using Splunk AI.
  • Interactive Dashboards: Create custom KPI displays using the dashboard editor. Click on visualizations to link to other dashboards, drill down and run new searches.
  • Reporting: Understand data using statistics and create advanced reports using the existing BI tech stack. Calculate typical values in a dataset using averages and medians. Measure how each value differs from the mean and each other.
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  • Data Visualizations: Includes built-in tools and panel configurations. In-memory data caching aids speed-of-thought analysis on large data volumes. Understand and exclude outliers and drill down into supporting reports using visual lasso filtering and zooming.  
  • Data Source: Build interactive analysis reports by using data from CSV files as well as relational and multidimensional data models. 
  • Data Integration: Flexible data ingestion ensures no limitation in terms of data type or source that’s accessible. Provides Extract, Transform, and Load (ETL) capabilities to capture, cleanse and store data using a uniform and consistent format. 
  • Reporting: View interactive reports in dashboards, with different capabilities such as column resizing and sorting, drag-and-drop report design, font selection, unlimited undo and redo functionality, and more. Export formats include HTML, PDF, CSV, Excel and Excel 93-2003. 
  • OLAP Analytics: Mondrian, an open-source business analytics engine, enables interactive data analysis in real time. Build business intelligence solutions as an Online Analytical Processing (OLAP) engine, enabling multidimensional queries against business data using the MDX query language. 
  • Data Modeling: Maps the physical structure of the database into a logical business model and Streamlined Data Refinery (SDR) using a relational data model. Helps augment and blend raw data through a request form to then be published. 
  • Data Transformation: Design transformations and jobs to run with a graphical user interface, executed in XML or in a database repository. A data transformation engine reads, writes and manipulates data to and from various sources. 
  • Role-Based Security: Restricts access to certain portions of a metadata model that are used as a data source. Offers table, column and row-level authorization control. 
  • Mobility: Get immediate access to business analysis at any time using a mobile app for iPad that uses touch navigation technology. 
  • Big Data Sources: Supports more than 15 big data sources such as Microsoft, Google Cloud, Apache Hive, MAPR and more.  
  • Data Model Integration: Integrate third-party models like R, Python, Scala with Spark MLlib and Weka into data flows. 
  • Integrations with Data Processing Distributions: Integrates Hadoop (and its distributions), NoSQL stores, log files, and JSON and XML data formats. 
  • Customization: A highly-customizable, web-based UI and its API integrations ensure complete control over look, feel and function. 
  • Tailored Training: Access architect-level staff with a proven track record of success with hundreds of customers. 
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Product Ranking

#3

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#12

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Business Analytics Tools

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User Sentiment Summary

Great User Sentiment 2623 reviews
Great User Sentiment 307 reviews
88%
of users recommend this product

Splunk has a 'great' User Satisfaction Rating of 88% when considering 2623 user reviews from 4 recognized software review sites.

81%
of users recommend this product

Pentaho has a 'great' User Satisfaction Rating of 81% when considering 307 user reviews from 4 recognized software review sites.

4.3 (410)
4.0 (47)
4.6 (227)
4.2 (39)
4.4 (1526)
4.0 (100)
4.4 (460)
4.1 (121)

Synopsis of User Ratings and Reviews

Data Visualization: About 92% of users mentioning dashboards praised its rich displays and many options to create custom views.
Functionality: Around 84% of users reviewing capabilities praised its rich feature set.
Ease of Use: Almost 65% of users citing user-friendliness praised the platform for making log analytics accessible.
Deployment: About 61% of users reviewing deployment said the system was easy to set up.
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Open-source and free core version: Makes Pentaho accessible to individuals and small teams, reducing initial investment costs.
Wide range of tools: Covers various data analysis needs, from basic reporting to advanced analytics, eliminating the need for multiple tools.
Scalable for large datasets: Handles growing data volumes efficiently, ensuring smooth performance for complex analyses.
Active community support: Provides valuable resources and troubleshooting assistance, especially for the open-source version.
Integration with various platforms: Connects seamlessly with existing data sources and BI tools, simplifying data workflows.
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Pricing: Around 96% of users mentioning cost found it expensive.
Learning Curve: Deep learning is required to use the platform, approximately 77% of users referencing training said.
Performance: About 61% of users reviewing performance said it slowed down when handling complex queries.
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Steeper learning curve: Compared to user-friendly options, Pentaho's interface and features might require more technical expertise to master.
Limited documentation: While resources exist, some users find the documentation incomplete or outdated, hindering troubleshooting and advanced usage.
Occasional bugs and glitches: Users report encountering bugs and glitches, especially in the open-source version, potentially impacting data analysis workflows.
Resource-intensive: Large-scale data processing and complex analyses can demand powerful hardware, increasing infrastructure costs.
Limited customization options: While customization is possible, some users crave more flexibility and control over the platform's look and feel.
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Splunk is a robust security and incident-monitoring platform for operations support. Event logs, alerts, security management and KPI tracking make it a robust enterprise solution. Search, storage and analysis are its strong points.We referenced online reviews for the past 18 months for this synopsis.About 92% of data workers said its incident review dashboard enables easy system monitoring. The capability to design dashboards with the option to drill down into data is an asset. Some users said they would like to have more visualizations.It garnered high praise for real-time incident monitoring. During our research, an oft-repeated sentiment was that users would not want to revert to previous tools.About 84% of knowledge workers reviewing functionality said the solution had substantial data collection and analysis capabilities. Around 65% of reviewers reported it was easy to use and had a readable log format.About 96% of the users citing pricing said it was costly but praised it for delivering on its promise and worth every penny. It can be complex to learn, and there’s a significant learning curve, according to around 77% of data workers who mentioned adoption.Slow loads and delayed responses were at the top of the minds of around 61% of users when discussing performance. According to Enlyft, mid-sized enterprises form a large chunk of the user base, and understandably so, as its steep price can deter small players.

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Reviews of Pentaho paint a picture of a powerful, open-source data platform with both promise and pitfalls. Many users cite its wide range of tools and impressive scalability as major strengths, allowing them to tackle diverse tasks without needing multiple products. "It's a Swiss Army knife for data," one reviewer enthusiastically declared. But this power comes with a caveat – a steeper learning curve compared to more user-friendly options like Tableau. "It's not drag-and-drop intuitive," another user cautioned. Documentation is another point of contention. While some praise the available resources, others lament it as incomplete or outdated, often requiring community forums for troubleshooting. This is where the strong, active community becomes a saving grace – a true differentiator for Pentaho compared to pricier competitors. "The community is like having a built-in support team," a user noted, highlighting the value of shared knowledge and collaboration. However, users also report occasional bugs and glitches, especially in the free Community Edition. This can be a frustration for those seeking enterprise-level stability. And while Pentaho handles large datasets admirably, its resource-intensive nature can demand costly hardware upgrades, a factor to consider against competitors with built-in cloud options. Overall, Pentaho emerges as a versatile platform for those willing to invest time in learning its intricacies. Its open-source nature and powerful toolset make it a budget-friendly choice for startups and data-savvy teams. But for those prioritizing user-friendliness and seamless workflows, alternatives might be more appealing. Ultimately, the choice boils down to balancing Pentaho's strengths and weaknesses against your specific needs and technical expertise.

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