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Comparison
Alternative to Splunk
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DataSnap vs Splunk

Splunk is a reference for SIEM and log management in complex environments. DataSnap prioritizes managed analysis/visualization with predictable costs, AI and fast setup without operating heavy stacks.

We keep the comparison updated, but exact prices must be confirmed directly on Splunk.

Official sources

References

Always validate directly in Splunk’s official documentation before any decision.

Reference: datasnap.cloud

DataSnap differentiators

Focus on logs & data
  • Operational simplicity
    Managed analysis and ready visualization without heavy stacks.
  • Predictable costs
    Clear model with automatic optimizations.
  • AI dashboards
    Natural language queries and SQL-like interface.
  • Native Oracle Cloud integration
    Object Storage with high durability.

Reference: datasnap.cloud

Positioning vs Splunk

Honest view
  • Enterprise SIEM vs managed focus
    Splunk is robust for SIEM/complex environments. DataSnap focuses on value with lower operational friction.
  • Pricing model
    Structures can be complex. DataSnap emphasizes predictability and direct spend control.
  • Time to value
    DataSnap offers agile API setup and AI dashboards.

When should you choose DataSnap over Splunk?

If SIEM operation is too heavy for your context, this summary helps see where DataSnap best fits.

Illustrative scenario
App + infra logs
Lean teams

Operational complexity may reduce time-to-value. DataSnap simplifies: ingestion + processing + retention, with ready visualization.

Important: validate compliance requirements that may demand full SIEM.

Ideal profiles
Where DataSnap shines
  • Managed analysis without operating complex stacks
  • Predictable costs
  • AI dashboards and simple queries
Be honest about your case
When Splunk still makes sense
  • Need for complete SIEM with deep integrations
  • Large-scale environments with advanced requirements

DataSnap aims to be the best option when cost and simplicity are priorities.

Próximo passo sugerido
  • Test a sample of logs in DataSnap and compare time-to-value
  • Use matching periods/log levels for a fair comparison
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