1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.