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

Filebeat vs Splunk

OverviewComparisonAlternatives

Overview

Splunk
Splunk
Stacks772
Followers1.0K
Votes20
Filebeat
Filebeat
Stacks133
Followers252
Votes0

Filebeat vs Splunk: What are the differences?

Introduction

Filebeat and Splunk are both popular tools used for log management and analysis. While they serve similar purposes, there are key differences between the two.

  1. Architecture: Filebeat is a lightweight data shipper that sends log data from sources to an Elasticsearch or Logstash backend. It collects log files and forwards them in near real-time. On the other hand, Splunk is a comprehensive log management and analytics platform that ingests, indexes, and analyzes log data within its own centralized system.

  2. Data Collection: Filebeat uses a modular approach and has predefined modules for different log types, making the collection process easier. It can also be configured to collect log data from different sources, including files, syslog, and network protocols. Splunk, on the other hand, supports log data collection from various sources but requires more manual configuration and setup.

  3. Scalability: Filebeat is designed for lightweight log shipping and can be easily scaled horizontally by adding more instances. It also has a smaller memory footprint compared to Splunk. Splunk, on the other hand, is capable of handling large-scale log data ingestion, indexing, and analysis through its distributed architecture. It offers more advanced features for managing and scaling log data in enterprise environments.

  4. Search and Analysis: Filebeat focuses primarily on collecting and shipping log data to a central backend for further analysis. It provides basic search capabilities but relies on external tools like Elasticsearch or Logstash for data indexing and querying. Splunk, on the other hand, offers a comprehensive search and analysis platform with a powerful search language, visualization capabilities, and built-in data analysis tools. It provides a user-friendly interface for exploring and analyzing log data within its own system.

  5. Alerting and Monitoring: Filebeat does not have built-in alerting and monitoring capabilities. It primarily handles log data collection and shipping. Splunk, on the other hand, offers advanced alerting and monitoring features. It allows users to set up alerts based on specific log patterns or conditions and provides real-time monitoring and reporting capabilities.

  6. Cost: Filebeat is open-source and free to use. It is a lightweight option suitable for small to medium-sized deployments. Splunk, on the other hand, is a commercial tool with different licensing options based on data volume and features. It can be more expensive, especially for large-scale deployments.

In summary, Filebeat is a lightweight log shipper that focuses on collecting and shipping log data, while Splunk is a comprehensive log management and analytics platform with advanced search, analysis, and monitoring capabilities. Splunk also offers more scalability and features, but comes at a higher cost compared to Filebeat.

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Detailed Comparison

Splunk
Splunk
Filebeat
Filebeat

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

It helps you keep the simple things simple by offering a lightweight way to forward and centralize logs and files.

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
772
Stacks
133
Followers
1.0K
Followers
252
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
Logstash
Logstash

What are some alternatives to Splunk, Filebeat?

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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