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  1. Stackups
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  3. LogDNA vs Splunk

LogDNA vs Splunk

OverviewComparisonAlternatives

Overview

Splunk
Splunk
Stacks621
Followers1.0K
Votes20
LogDNA
LogDNA
Stacks101
Followers144
Votes18

LogDNA vs Splunk: What are the differences?

  1. Setup and Configuration: LogDNA provides a simple and straightforward setup process, with configuration made easy through its intuitive user interface. On the other hand, Splunk requires more complex configuration with multiple components and settings to be managed.
  2. Ease of Use: LogDNA offers a user-friendly interface that focuses on simplicity and ease of use, making it suitable for users of all levels. In comparison, Splunk has a steeper learning curve and requires more technical expertise to navigate and utilize its advanced features effectively.
  3. Pricing and Scalability: LogDNA offers transparent, straightforward pricing based on data volume, making it more predictable and easier to plan for cost-wise. Splunk's pricing is more complex and can be costly, especially for larger-scale deployments. Additionally, LogDNA provides built-in scalability, allowing users to easily handle increasing data volumes without significant additional setup, whereas Splunk may require additional infrastructure and licenses to scale effectively.
  4. Integrations and Ecosystem: LogDNA has a growing list of integrations with popular tools and platforms, making it easier to incorporate into existing workflows. Splunk, on the other hand, has a wider range of integrations and a more mature ecosystem, offering greater flexibility and compatibility with various systems and technologies.
  5. Analytics and Data Insights: Splunk offers advanced analytics features, including machine learning capabilities and sophisticated data visualization, enabling users to gain deeper insights from their log data. While LogDNA offers basic analytics and filtering capabilities, it may not provide the same level of depth and customization as Splunk.
  6. Support and Community: Both LogDNA and Splunk offer support options, including online documentation, knowledge bases, and customer support teams. However, Splunk, being a more established and widely adopted product, has a larger community and user base, providing users with more extensive resources, forums, and community-driven support.

In summary, LogDNA provides a simpler setup and user experience, transparent pricing, and ease of scalability, while Splunk offers more advanced analytics capabilities, a wider range of integrations, and a larger support community.

Detailed Comparison

Splunk
Splunk
LogDNA
LogDNA

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

The easiest log management system you will ever use! LogDNA is a cloud-based log management system that allows engineering and devops to aggregate all system and application logs into one efficient platform. Save, store, tail and search app

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
Aggregate Logs & Analyze Related Events;Easy Setup in Minutes;Powerful Search & Alerts;Save what you see as a View;Modern User Interface;Tail -f Like a Boss;Debug & Troubleshoot Faster
Statistics
Stacks
621
Stacks
101
Followers
1.0K
Followers
144
Votes
20
Votes
18
Pros & Cons
Pros
  • 3
    API for searching logs, running reports
  • 3
    Alert system based on custom query results
  • 2
    Ability to style search results into reports
  • 2
    Splunk language supports string, date manip, math, etc
  • 2
    Query engine supports joining, aggregation, stats, etc
Cons
  • 1
    Splunk query language rich so lots to learn
Pros
  • 6
    Easy setup
  • 4
    Cheap
  • 3
    Extremely fast
  • 2
    Powerful filtering and alerting functionality
  • 1
    Graphing capabilities
Cons
  • 1
    Cannot copy & paste text from visualization
  • 1
    Limited visualization capabilities

What are some alternatives to Splunk, LogDNA?

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.

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.

Sematext

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

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