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Splunk vs Tableau: What are the differences?


In this article, we will explore the key differences between Splunk and Tableau. Both Splunk and Tableau are powerful data analytics tools, but they differ in several ways.

  1. Deployment and Purpose: Splunk is primarily used as a log management and analysis platform, while Tableau is a data visualization and business intelligence tool. Splunk is designed to process and analyze machine-generated data, such as log files, enabling organizations to gain insights into operational and security issues. On the other hand, Tableau focuses on data visualization and reporting, helping users create interactive dashboards and reports from various data sources.

  2. Data Integration and Sources: Splunk excels in ingesting and indexing data from diverse sources, including log files, web servers, databases, and cloud platforms. It has built-in connectors and integrations for seamless data collection. Tableau, on the other hand, supports data integration from various sources but requires some additional configurations or connectors. It can connect to data from databases, spreadsheets, cloud services, and big data platforms.

  3. Data Analysis Capabilities: Splunk provides advanced search, analysis, and correlation functionalities for large-scale data processing. It allows users to apply complex queries, perform statistical analysis, and create alerts based on predefined conditions. Tableau, however, offers a wide range of data manipulation and analytics capabilities, such as data blending, forecasting, and advanced statistical modeling. It enables users to explore data visually, create hierarchies, and perform calculations using a drag-and-drop interface.

  4. User Interface and Interactive Visualization: Tableau has a highly intuitive and user-friendly interface, making it easy for non-technical users to create interactive visualizations and reports. It offers a wide range of chart types, maps, and filters to enhance data exploration. Splunk, although powerful, has a steeper learning curve due to its query-based interface and extensive search processing capabilities. It is more suitable for technical users and data analysts.

  5. Scalability and Performance: Splunk is known for its ability to handle massive volumes of data efficiently. It can scale horizontally across multiple nodes for high availability and distributed processing. Tableau, on the other hand, may face performance limitations when dealing with very large datasets or complex calculations. It requires robust hardware and optimized query designs to ensure optimal performance.

  6. Cost and Licensing Model: Splunk has a proprietary licensing model based on the amount of data ingested and the number of user licenses. It can become expensive for organizations with large data volumes or a high number of users. Tableau offers both a desktop version for individual users and a server version for enterprise deployments. The cost of Tableau varies based on the number of users and the deployment options.

In summary, Splunk primarily focuses on log management and analysis, excels in handling machine-generated data, and offers extensive search and analysis capabilities. On the other hand, Tableau is a data visualization and business intelligence tool that provides a user-friendly interface, interactive visualizations, and broad data integration options.

Decisions about Splunk and Tableau

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

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Vojtech Kopal
Head of Data at Mews Systems · | 3 upvotes · 307.4K views

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

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Pros of Splunk
Pros of Tableau
  • 3
    API for searching logs, running reports
  • 3
    Alert system based on custom query results
  • 2
    Dashboarding on any log contents
  • 2
    Custom log parsing as well as automatic parsing
  • 2
    Ability to style search results into reports
  • 2
    Query engine supports joining, aggregation, stats, etc
  • 2
    Splunk language supports string, date manip, math, etc
  • 2
    Rich GUI for searching live logs
  • 1
    Query any log as key-value pairs
  • 1
    Granular scheduling and time window support
  • 6
    Capable of visualising billions of rows
  • 1
    Intuitive and easy to learn
  • 1

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Cons of Splunk
Cons of Tableau
  • 1
    Splunk query language rich so lots to learn
  • 2
    Very expensive for small companies

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What is Splunk?

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

What is Tableau?

Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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What companies use Splunk?
What companies use Tableau?
See which teams inside your own company are using Splunk or Tableau.
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What tools integrate with Splunk?
What tools integrate with Tableau?

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What are some alternatives to Splunk and Tableau?
Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Sumo Logic
Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight.
Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.
See all alternatives