Elastic vs. Grafana

AI-powered log streams with automatic parsing of raw signals.

Log streaming via Loki requires manual pipeline configuration and manual label schema design. No AI-based automatic parsing.

Automatic import included.

No automatic import. Each data source requires manual Grafana Agent or Alloy configuration.

450+ integrations with a single unified onboarding experience.

500+ integrations available, though split across solutions without a unified experience.

Streams: AI-based parsing of raw signals, zero schema design required.

Loki requires manual label schema design up front. No AI-based automatic parsing of raw log signals. Object storage looks cheaper on the ingest bill, but the savings disappear when you account for the engineering cost of designing and maintaining label schemas and the reingestion cost when schemas change.

Elastic AI Agent uses your enterprise knowledge and open LLM connectors for accurate, grounded answers. Your agents can use the MCP to query Elastic metrics, logs, and traces directly.

Root cause analysis across physically separate Loki, Tempo, and Mimir back ends remains limited by the absence of a shared data model.

Enterprise knowledge integrations included.

No enterprise knowledge integrations for AI-powered investigations.

Managed LLM (no setup) or open connectors to OpenAI, Azure OpenAI, Amazon Bedrock, and Google Gemini.

Limited LLM provider support. No open connectors to Bedrock, Azure OpenAI, or Gemini at the same depth as Elastic.

Significant Events surfaces meaningful signals in logs automatically.

No significant events capability.

100+ preconfigured anomaly detection jobs across all signals — logs, metrics, traces — using both unsupervised and supervised techniques.

ML-based anomaly detection available primarily for metrics. No preconfigured detection jobs across logs, traces, and all signal types.

Unified APM and universal profiling in one platform.

Full APM via Application Observability; however, traces (Tempo), metrics (Mimir), and logs (Loki) remain on separate back ends requiring manual correlation.

Built-in eBPF-based continuous code profiling.

Beyla (eBPF auto-instrumentation) + Pyroscope (continuous profiling) available as separate products requiring additional deployment.

Infrastructure monitoring included with unified auto-discovery.

Available via separate Grafana Agent/Alloy configuration. No unified auto-discovery.

Synthetic monitoring included.

Synthetic monitoring available (k6 + Grafana Synthetic Monitoring) as a separate product.

SLOs supported.

SLOs only supported in Grafana Cloud.

Proactive alerts based on anomaly detection across the full user journey.

Dynamic alerting via ML forecasting for metrics only. No proactive anomaly-based alerting across all signal types and the full user journey.

Cases built into core observability workflow.

Grafana IRM available as a separate add-on product.

Inference API with built-in semantic models included.

No inference API with built-in semantic models.

First-class search: fuzziness, synonyms, highlighting, and nested queries at petabyte scale.

Basic log search only. No fuzzy search, semantic search, or synonym support. Search experience degrades at scale.

Fine-grained RBAC with custom roles, spaces, and document-level and field-level security.

Limited RBAC is available in Grafana Cloud. No document-level or field-level security for regulated industry data isolation.

Fine-grained access control with document-level and field-level masking.

Coarse-grained access controls. No document-level or field-level masking for sensitive data in regulated environments.

Global managed service + fully managed + self-managed (on-premises, hybrid, air-gapped).

Grafana Cloud is globally available, but there is no true on-premises or air-gapped deployment in the managed offering.

Fully managed service with existing FedRAMP authorization on the same platform used by commercial customers.

Grafana Federal Cloud is FedRAMP High authorized, but it is a separate, dedicated product from mainstream Grafana Cloud. Regulated customers must choose between the federal SKU or the commercial platform; there is no unified offering.

Built for petabyte-scale indexing and aggregations with full-fidelity retention.

Loki's label-based indexing breaks down under high-cardinality workloads common in modern cloud-native stacks. Grafana's Adaptive Telemetry reduces ingest volume by selectively dropping data not by intelligently preserving signal. Each component also scales independently, multiplying the operational surface.

One-click setup, integrated UI, low operational overhead. The Express Migration program helps quantify and reduce hidden costs when switching.

Self-managed Grafana (LGTM): five separate products to deploy, tune, upgrade, and scale. Real TCO includes SRE hours spent designing Loki label schemas, tuning Mimir retention, scaling Tempo separately, and managing five separate upgrade cycles. Grafana Cloud removes deployment burden but does not eliminate schema design complexity or multi-query-language overhead.

Full geospatial search, geo hexgrids, and map visualizations.

Basic geo map visualization via Grafana panels. No full geospatial search, hexgrids, or spatial query capabilities.

First-class search: fuzziness, synonyms, highlighting, and nested queries.

Grafana is a visualization tool, not a search platform. No full-text search, fuzzy search, semantic search, or synonym support.