Apache Storm
Current- Annual cost
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- Seats assigned
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This catalog view compares public market data and does not include organization spend or usage.
ALTERNATIVE APPLICATIONS
Apache Storm Alternatives
Should you replace Apache Storm?
Apache Spark is the strongest catalog alternative to evaluate for Apache Storm.
Apache Storm alternatives
See how Apache Storm compares to 5 alternative apps you can switch to.
Apache Spark and Apache Flink selected for comparison.
Annual costTotal subscription cost for each app, shown for the selected billing period.
Apache St...
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Apache Storm
Public catalog pricing. Organization spend is not included.
Apache Sp...
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Public pricing
Public catalog pricing estimate.
Apache Fl...
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Public pricing
Public catalog pricing estimate.
3-Year Net SavingEstimated savings over three years after migration and setup costs.
Apache St...
$0
No migration in the current app baseline.
Apache Sp...
--
After $35,000 estimated migration cost.
Apache Fl...
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After $15,000 estimated migration cost.
Team Fit ScoreHow closely the app matches the teams, workflows, and usage patterns currently in place.
Apache St...
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Apache Sp...
78/100
Data engineering teams building unified batch and streaming pipelines with machine learning will find Spark's ecosystem significantly more productive than Storm's single-purpose design. However, teams requiring sub-100ms latency on individual events will struggle with Spark's micro-batch architecture. Engineering teams with strong Scala or Python skills adopt faster than those tied to Storm's Java-centric topology model.
Apache Fl...
75/100
Apache Flink suits data platform teams building complex stateful analytics and event-time processing pipelines that outgrow Storm's at-least-once semantics. Teams requiring exactly-once guarantees and unified batch/stream processing will see immediate value, while those with simple DAGs will struggle with Flink's operational complexity and JVM tuning requirements.
Adoption RiskExpected friction, training effort, and behavior change needed to move teams onto the alternative.
Apache St...
--
Public adoption signal for the current app.
Apache Sp...
low
Apache Spark is a high-complexity migration. Estimated 10 weeks and $35,000 one-time cost.
Apache Fl...
low
Apache Flink is a high-complexity migration. Estimated 8 weeks and $15,000 one-time cost.
User satisfactionAvailable rating and review signal for team sentiment around the app.
Apache St...
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42 reviews
Apache Sp...
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Apache Fl...
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Timeline & DisruptionExpected migration duration and disruption to normal workflows.
Apache St...
No migration needed
Apache Sp...
10 weeks
High
Apache Spark is a high-complexity migration. Estimated 10 weeks and $35,000 one-time cost.
Apache Fl...
8 weeks
High
Apache Flink is a high-complexity migration. Estimated 8 weeks and $15,000 one-time cost.
Setup & trainingOne-time implementation, enablement, and training investment required.
Apache St...
--
Apache Sp...
$35,000
Estimated one-time migration and setup effort.
Apache Fl...
$15,000
Estimated one-time migration and setup effort.
Integration CoverageHow much of the current integration and workflow surface is covered by the app.
Apache St...
100%
Supports 80 native integrations.
Apache Sp...
--
Apache Fl...
--
Feature Match (%)How closely the app matches current feature needs, including notable gaps or risks.
Apache St...
100%
Apache Sp...
0%
- Micro-batch processing introduces higher latency than Storm's record-at-a-time model
- Requires complete rewrite of spout/bolt topologies to RDD or DataFrame APIs
- Heavier memory footprint for in-memory computation across clusters
- Complex tuning required for batch interval and checkpointing balance
- Exactly-once semantics harder to implement than Storm's at-least-once
Apache Fl...
0%
- Higher operational complexity for state backend management
- Memory-intensive JVM tuning required for large state
- Steeper learning curve for checkpointing and savepoints
- Limited Storm topology compatibility without code rewrites
CertificationsSecurity, privacy, and compliance certifications available for each app.
Apache St...
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Apache Sp...
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Apache Fl...
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Choose This IfThe conditions where keeping or switching to this app is likely to make sense.
Apache St...
You already standardize on this app.
Apache Sp...
You need unified analytics pipelines combining streaming, batch processing, SQL, and machine learning in one framework
Apache Fl...
You require exactly-once semantics, complex stateful operations, or unified batch/stream processing with modern SQL support
Avoid This IfThe conditions where this app is likely to create cost, workflow, or adoption risk.
Apache St...
Public pricing or fit signals no longer match your needs.
Apache Sp...
You require millisecond-level latency on individual event processing or run lightweight edge deployments
Apache Fl...
You prioritize operational simplicity and fast deployment over advanced state management and event-time processing capabilities
