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Comparison
Alternative to Grafana Loki
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DataSnap vs Grafana Loki

Grafana Loki aggregates logs with label‑based indexing to reduce indexing costs. DataSnap focuses on managed analysis/visualization with predictable costs and AI, without maintaining extra components.

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

Official sources

References

We recommend validating directly in Grafana’s official documentation before any decision.

Reference: datasnap.cloud

DataSnap differentiators

Focus on logs & data
  • Managed analysis
    Ready platform to search, filter and visualize data.
  • Predictable costs
    Clear model with automatic optimizations.
  • AI dashboards
    Natural language queries and SQL‑like interface.

Reference: datasnap.cloud

Positioning vs Grafana Loki

Honest view
  • Labels vs ready visualization
    Loki optimizes indexing via labels. DataSnap delivers ready visualization with AI.
  • Operation
    Loki often requires operating components. DataSnap reduces friction with a managed service.

When should you choose DataSnap over Grafana Loki?

If operating Loki and its stack is heavy for your team, this summary helps see where DataSnap best fits.

Illustrative scenario
App + infra logs
Value focus

Operating components consumes time. DataSnap simplifies: ingestion + processing + retention.

Important: consider specific observability requirements.

Ideal profiles
Where DataSnap shines
  • Teams wanting managed analysis without operating Loki or pipelines
  • Need for predictable costs and retention governance
  • Per‑client/tenant consumption separation with transparency
Be honest about your case
When Grafana Loki still makes sense
  • You need to reduce indexing cost with labels and already operate Loki well
  • Dependence on Grafana stack with deep integrations
  • Team masters Loki and prefers to keep current architecture

DataSnap complements when managed analysis and predictable costs are the priority.

Próximo passo sugerido
  • Start with 1 service to compare consumption and analysis
  • Use matching periods/log levels for a fair comparison
  • Evaluate partial migration or hybrid use with Loki