Embulk vs Logstash

Overview

Logstash

Stacks12.3K

Followers8.8K

Votes103

GitHub Stars14.7K

Forks3.5K

Embulk

Stacks27

Followers26

Votes0

GitHub Stars1.8K

Forks202

Embulk vs Logstash: What are the differences?

Data Processing: Embulk is optimized for bulk loading and transforming data before importing it into a database, while Logstash is built for processing and transferring log data from various sources to a centralized repository. Embulk focuses on transforming large datasets efficiently, while Logstash specializes in real-time log parsing and enrichment.
Language Support: Embulk provides native support for Java-based plugins, making it easier to extend its functionality using Java libraries. On the other hand, Logstash relies on Ruby for its plugin system, which may require additional dependencies and customization for integration with non-Ruby environments.
Community and Ecosystem: Logstash, being a part of the Elastic stack, has a larger and more active community with extensive documentation and support resources. Embluk, while growing, may have a smaller community and fewer pre-built plugins available compared to Logstash.
Scalability: Logstash is designed to be highly scalable and can be easily clustered for handling large volumes of data across distributed systems. Embulk, on the other hand, may require additional configuration and orchestration tools for achieving the same level of scalability.
Architecture: Embulk follows a pluggable architecture, where each stage of the data processing pipeline can be customized with different plugins. In contrast, Logstash uses a more rigid pipeline architecture with predefined stages for input, filters, and output, providing a more straightforward configuration but potentially limiting flexibility in complex workflows.
Performance: In terms of performance, Embulk is known for its efficient memory management and parallel processing capabilities, making it suitable for large-scale batch processing tasks. Logstash, while capable of real-time data processing, may have higher memory and CPU overhead due to its architecture and feature set.

In Summary, Embulk and Logstash differ in their focus on data processing, language support, community and ecosystem, scalability, architecture, and performance, catering to different use cases and requirements.

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CLI (Node.js)

Manual

Detailed Comparison

Logstash	Embulk
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.	It is an open-source bulk data loader that helps data transfer between various databases, storages, file formats, and cloud services.
Centralize data processing of all types;Normalize varying schema and formats;Quickly extend to custom log formats;Easily add plugins for custom data source	Automatic guessing of input file formats; Parallel & distributed execution to deal with big data sets; Transaction control to guarantee All-or-Nothing; Resuming; Plugins released on RubyGems.org
Statistics
GitHub Stars 14.7K	GitHub Stars 1.8K
GitHub Forks 3.5K	GitHub Forks 202
Stacks 12.3K	Stacks 27
Followers 8.8K	Followers 26
Votes 103	Votes 0
Pros & Cons
Pros 69 Free 18 Easy but powerful filtering 12 Scalable 2 Kibana provides machine learning based analytics to log 1 Well Documented Cons 4 Memory-intensive 1 Documentation difficult to use	No community feedback yet
Integrations
Kibana Elasticsearch Beats	Java GitHub macOS JSON

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Postman

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Papertrail

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Logmatic

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Loggly

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Paw

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Logentries

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Karate DSL

Combines API test-automation, mocks and performance-testing into a single, unified framework. The BDD syntax popularized by Cucumber is language-neutral, and easy for even non-programmers. Besides powerful JSON & XML assertions, you can run tests in parallel for speed - which is critical for HTTP API testing.

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.

Appwrite

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Runscope

Keep tabs on all aspects of your API's performance with uptime monitoring, integration testing, logging and real-time monitoring.

Related Comparisons

Embulk vs Logstash: What are the differences?

Data Processing: Embulk is optimized for bulk loading and transforming data before importing it into a database, while Logstash is built for processing and transferring log data from various sources to a centralized repository. Embulk focuses on transforming large datasets efficiently, while Logstash specializes in real-time log parsing and enrichment.
Language Support: Embulk provides native support for Java-based plugins, making it easier to extend its functionality using Java libraries. On the other hand, Logstash relies on Ruby for its plugin system, which may require additional dependencies and customization for integration with non-Ruby environments.
Community and Ecosystem: Logstash, being a part of the Elastic stack, has a larger and more active community with extensive documentation and support resources. Embluk, while growing, may have a smaller community and fewer pre-built plugins available compared to Logstash.
Scalability: Logstash is designed to be highly scalable and can be easily clustered for handling large volumes of data across distributed systems. Embulk, on the other hand, may require additional configuration and orchestration tools for achieving the same level of scalability.
Architecture: Embulk follows a pluggable architecture, where each stage of the data processing pipeline can be customized with different plugins. In contrast, Logstash uses a more rigid pipeline architecture with predefined stages for input, filters, and output, providing a more straightforward configuration but potentially limiting flexibility in complex workflows.
Performance: In terms of performance, Embulk is known for its efficient memory management and parallel processing capabilities, making it suitable for large-scale batch processing tasks. Logstash, while capable of real-time data processing, may have higher memory and CPU overhead due to its architecture and feature set.

Embulk vs Logstash

Overview