What are the key differences between Elastic Stack (ELK) and Apache Spark?

Compare Elastic Stack (ELK) and Apache Spark side by side on Lunoo to see detailed feature differences, AI scores, and expert analysis.

How are Elastic Stack (ELK) and Apache Spark scored?

Elastic Stack (ELK) has an AI score of 8.5/10 and Apache Spark has an AI score of 9.2/10. Scores are based on category fit, feature coverage, pricing signals, public reception, and recency.

Elastic Stack (ELK) vs Apache Spark 2026 — Compared

Elastic Stack (ELK)

Apache Spark

WINNER Apache Spark

Apache Spark edges ahead with a score of 9.2/10 compared to 8.5/10 for Elastic Stack (ELK). While both are highly rated...

Elastic Stack (ELK)

8.5 Very Good

Data Analysis Get Elastic Stack (ELK) open_in_new

emoji_events WINNER

Apache Spark

9.2 Excellent

Data Analysis Get Apache Spark open_in_new

Elastic Stack (ELK) From Free (selfhosted); from $0.20/GB per month (Elastic Cloud) Free plan available

payments

Apache Spark Free plan available

psychology AI Verdict

Apache Spark edges ahead with a score of 9.2/10 compared to 8.5/10 for Elastic Stack (ELK). While both are highly rated in their respective fields, Apache Spark demonstrates a slight advantage in our AI ranking criteria. A detailed AI-powered analysis is being prepared for this comparison.

emoji_events Winner: Apache Spark

verified Confidence: Low

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description Overview

Elastic Stack (ELK)

The Elastic Stack, consisting of Elasticsearch, Logstash, and Kibana, is the most widely used open-source log management solution. It provides powerful full-text search capabilities, making it ideal for complex data exploration and visualization. Kibana offers a rich UI for building dashboards, while Elasticsearch provides the engine for lightning-fast queries. While it requires significant effort...

Apache Spark

Apache Spark is the industry standard for large-scale data processing. While it is a general-purpose engine, its SQL module (Spark SQL) is a powerful query engine capable of handling petabyte-scale datasets. Spark is designed for distributed computing, making it the primary choice for heavy ETL pipelines and complex batch analytics. Its ability to integrate with various data sources and its massiv...