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

Scribe vs Splunk

OverviewComparisonAlternatives

Overview

Splunk
Splunk
Stacks772
Followers1.0K
Votes20
Scribe
Scribe
Stacks36
Followers31
Votes0
GitHub Stars3.9K
Forks787

Scribe vs Splunk: What are the differences?

Introduction

This Markdown document provides the key differences between Scribe and Splunk, two commonly used tools in the field of log management and analysis.

  1. Data Collection and Integration: Scribe focuses on providing a simple and lightweight solution for log collection and integration. Its primary function is to extract log data from various sources and transport it to other destinations, such as databases or analytics tools. Splunk, on the other hand, offers a comprehensive platform for collecting and indexing log data from various sources, providing a more robust and feature-rich data collection and integration solution.

  2. Search and Analysis Capabilities: Splunk offers powerful search and analysis capabilities, allowing users to explore and analyze log data using its proprietary Splunk search language. It provides advanced search functionalities, including real-time search and statistical analysis. Scribe, on the other hand, focuses more on data transport rather than search and analysis, and it does not provide advanced search functionalities like Splunk.

  3. Scalability and Performance: Splunk is designed to handle large volumes of log data and can scale horizontally by adding more indexing nodes. It offers distributed search capabilities, allowing users to distribute search and analysis workload across multiple nodes. Scribe, on the other hand, is more lightweight and may not be as scalable or performant for large-scale log data processing as Splunk.

  4. User Interface and Visualization: Splunk provides a user-friendly web-based interface for data exploration, search, and visualization. It allows users to create dashboards, charts, and reports to gain insights from log data. Scribe, being primarily a log collection and transport tool, does not provide a built-in user interface or data visualization capabilities like Splunk.

  5. Cost and Licensing: Scribe is an open-source tool and is available under the Apache License, which means it can be used and modified freely without any licensing cost. Splunk, on the other hand, is a commercial product with different licensing options, including free and paid versions. The cost and licensing of Splunk depend on the volume of log data and specific features required.

  6. Community and Ecosystem: Splunk has a large and active community, with extensive documentation, user forums, and a marketplace for third-party apps and integrations. It offers a wide range of plugins and connectors to integrate with various data sources and systems. Scribe, being an open-source tool, also has a community-driven ecosystem with community support and available plugins, but it may not be as extensive as the Splunk ecosystem.

In summary, Scribe focuses on lightweight log collection and data transport capabilities, while Splunk provides a more comprehensive platform with advanced search, analysis, visualization, scalability, and community support, among other features. The choice between the two depends on specific requirements, budget, and the complexity of log management and analysis needs.

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Detailed Comparison

Splunk
Splunk
Scribe
Scribe

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

It is a server for aggregating log data streamed in real time from a large number of servers. It is designed to be scalable and reliable.

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
Aggregating log data ;Streamed in real time
Statistics
GitHub Stars
-
GitHub Stars
3.9K
GitHub Forks
-
GitHub Forks
787
Stacks
772
Stacks
36
Followers
1.0K
Followers
31
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
Python
Python
Hadoop
Hadoop
Apache Thrift
Apache Thrift

What are some alternatives to Splunk, Scribe?

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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