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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. DOMO vs Splunk

DOMO vs Splunk

OverviewComparisonAlternatives

Overview

Splunk
Splunk
Stacks773
Followers1.0K
Votes20
DOMO
DOMO
Stacks52
Followers75
Votes0

DOMO vs Splunk: What are the differences?

In today's data-driven world, organizations are leveraging tools like DOMO and Splunk to make sense of vast amounts of data. Here, we will highlight the key differences between these two powerful platforms.

  1. Data Source Integration: DOMO offers seamless integration with numerous data sources, such as databases, cloud applications, and spreadsheets, enabling users to bring in data from various sources with ease. On the other hand, Splunk is primarily focused on machine-generated data, making it a robust choice for analyzing log files, network traffic, and other IT-centric data sources.

  2. Visualization Capabilities: DOMO excels in providing visually appealing and interactive dashboards that enable users to gain insights quickly through graphs, charts, and real-time data visualization. In contrast, Splunk offers rich visualization options but leans more towards technical and detailed views suitable for IT monitoring and troubleshooting.

  3. User Interface and Ease of Use: DOMO is known for its intuitive and user-friendly interface, making it accessible to users across different departments without much training. Splunk, while powerful, has a steeper learning curve, requiring users to have some technical expertise to fully utilize its capabilities.

  4. Price Model: DOMO follows a subscription-based pricing model, where users pay per user per month, with additional costs for premium features and add-ons. Splunk, on the other hand, has a more complex pricing structure based on data volume ingested, making it more suitable for organizations with specific data management needs and budgets.

In Summary, DOMO and Splunk differ in terms of data source integration, visualization capabilities, user interface, ease of use, and pricing model, catering to different user requirements and organizational purposes.

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Detailed Comparison

Splunk
Splunk
DOMO
DOMO

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

Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform.

Predict and prevent problems with one unified monitoring experience; Streamline your entire security stack with Splunk as the nerve center; Detect, investigate and diagnose problems easily with end-to-end observability
-
Statistics
Stacks
773
Stacks
52
Followers
1.0K
Followers
75
Votes
20
Votes
0
Pros & Cons
Pros
  • 3
    Alert system based on custom query results
  • 3
    API for searching logs, running reports
  • 2
    Ability to style search results into reports
  • 2
    Query engine supports joining, aggregation, stats, etc
  • 2
    Dashboarding on any log contents
Cons
  • 1
    Splunk query language rich so lots to learn
No community feedback yet
Integrations
No integrations available
Box
Box
Loggly
Loggly
Basecamp
Basecamp
HipChat
HipChat
Asana
Asana
Google BigQuery
Google BigQuery
Amazon Redshift
Amazon Redshift
Mailchimp
Mailchimp
HubSpot
HubSpot
GitHub
GitHub

What are some alternatives to Splunk, DOMO?

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Logentries

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Graylog

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

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