Free Datadog Alternative: 7 Open-Source and Hosted Options

A free Datadog alternative can mean open-source software on infrastructure you operate, a no-license-cost self-managed edition with a non-OSS license, or a hosted plan with usage limits. Those choices have very different costs and capabilities. None makes storage, upgrades, incident response, or engineering time disappear.

Fluxtail publishes this comparison. It is excluded from the table because it has paid Starter and Pro self-service plans only. If a no-cost requirement is not fixed, see the broader Datadog alternatives comparison.

The options below are not ranked. They are grouped by what they can replace: a multi-signal observability platform, a log and search system, or a limited hosted deployment. Current licenses and plan boundaries were checked on September 15, 2026.

Start by defining what “free” must cover

Datadog spans infrastructure monitoring, logs, traces, application performance, user experience, security, and other separately metered products. Its current pricing catalog uses several billing dimensions, including hosts, containers, data volume, indexed data, custom metrics, and product-specific units. A replacement does not need every Datadog feature, but it must cover the signals and investigation paths the team actually uses.

Three cost models appear in this comparison:

• Open-source, self-hosted: there is no software license charge for the open-source components. The operator pays for compute, storage, networking, backups, upgrades, security, and on-call ownership.
• No-cost, source-available edition: the software can be used without a license fee, but its license is not approved as open source by the Open Source Initiative or some capabilities remain under a separate commercial license.
• Hosted allowance: the vendor operates the platform and includes limited usage. Retention, ingest, users, governance, support, or AI features can become paid boundaries.

Before shortlisting anything, inventory the current Datadog deployment by signal, retention, daily ingest, indexed fields, dashboards, alerts, integrations, access rules, archives, and API or agent workflows. A metrics-only tool is not a full-stack substitute. A logs-only platform does not replace APM. A component stack may cover all three signals while still requiring several independent services.

Free Datadog alternatives at a glance

The table describes software access, not total cost. High availability, object storage, database backups, cross-region transfer, security patching, and the hours spent restoring a failed cluster all belong in the budget.

Self-hosted options that cover multiple signals

SigNoz Community

SigNoz Community is a close functional shape when the goal is one self-hosted interface for logs, metrics, traces, application exceptions, dashboards, and alerts. The current SigNoz overview describes an OpenTelemetry-powered platform with separate Logs, Metrics, and Trace explorers. Its Logs Explorer provides quick filters, field operators, AND/OR expressions, list, time-series, and table views, plus a live view.

Community Edition is installed and managed by the operator. The current Docker installation guide labels it self-hosted Community without a license, while the repository licenses core code under MIT Expat and keeps enterprise directories under a separate license. The practical cost is ClickHouse and application capacity, persistent storage, backup and restore, upgrades, collector health, and availability. The pricing comparison places advanced security and governance features in Enterprise, so verify identity, SSO, and access requirements before migration.

SigNoz also documents an MCP server for Cloud and self-hosted deployments. For self-hosting, the operator runs the server and supplies a service-account API key. The current MCP reference includes queries and mutations such as creating, updating, and deleting dashboards and alert rules; some tools require newer SigNoz versions. Only administrators can create the API keys described in that setup. Treat the service account's access as the authorization boundary, keep the endpoint private, and do not expose write tools to an agent that should only investigate.

SigNoz fits when OpenTelemetry is already the collection standard and the team is prepared to operate a stateful multi-signal backend. It is less suitable when the main goal is to remove observability operations from the on-call workload.

Grafana OSS with Prometheus, Loki, and Tempo

The Grafana open-source ecosystem is a component stack rather than one Datadog replacement. Prometheus stores and queries metrics, Loki stores logs, Tempo stores traces, Grafana provides the user interface and alerting, and Alloy or the OpenTelemetry Collector moves data. Grafana documents these as separate open-source projects, each with its own capacity and failure model.

The search experience depends on the signal. PromQL handles metrics, LogQL handles Loki labels and log content, and TraceQL handles Tempo traces. Grafana's Loki data-source documentation includes Explore, live tail, Logs Drilldown, field parsing, and alerting. This is flexible and familiar for cloud-native teams, but it is not a single universal query model. Label design is especially important: stable dimensions such as service and environment belong in labels, while request IDs and other high-cardinality values usually do not.

Grafana, Loki, and Tempo are licensed under AGPLv3; Prometheus is Apache 2.0. Operating the stack means sizing and upgrading several services, protecting internal endpoints, configuring object storage and retention, testing backups, and preserving correlations across signal schemas. Loki's installation guide also states that Loki has no built-in authentication layer, so an authenticating proxy or equivalent control is required.

The open-source Grafana MCP server works with self-hosted Grafana 9 or later. Its current documentation uses a Grafana service-account token or username and password, and each tool relies on Grafana RBAC. The catalog includes read tools and mutations for dashboards, folders, alerting, snapshots, incidents, and related resources. Disabling tool categories reduces exposure and context; it does not replace least-privilege service-account scopes.

This stack fits teams that already operate Prometheus or Grafana and want composable control. It is a poor cost-saving move when nobody owns its storage, cardinality, upgrades, and restore procedures.

OpenObserve Open Source

OpenObserve Open Source packages logs, metrics, traces, dashboards, pipelines, alerts, and a modern search UI into one self-hosted product. Its current documentation describes SQL and full-text log search, PromQL for metrics, OTLP ingestion, saved views, dashboards, and alerts. The search API requires a time range and supports filters, aggregation, and full-text functions, which makes query scope visible rather than hiding scan cost.

The open-source core uses AGPLv3, while Enterprise is separately licensed. Self-hosting still requires object storage or local storage design, metadata durability, compaction, backups, upgrades, and resource monitoring. Edition boundaries are important: current log documentation says custom-role RBAC that restricts logs per stream and role is available in Enterprise and Cloud; Open Source users have access to all logs.

OpenObserve's MCP server is available in the open-source edition. Its MCP documentation uses Basic authentication for OSS and an organization-specific endpoint. The tool catalog can query logs, metrics, and traces and can also create or delete streams, alerts, and users. The same documentation warns that OSS tool calls run with the connected account's full privileges because granular custom-role permissions are an Enterprise or Cloud feature. Use a dedicated account, isolate the MCP endpoint at the network layer, and require confirmation for every mutation. OAuth sign-in through Dex is also an Enterprise capability, not an OSS assumption.

OpenObserve fits when a compact, SQL-oriented multi-signal system is attractive and the OSS access model is acceptable. It should not be selected before testing failure recovery, long-range query cost, role separation, and upgrade behavior with realistic data.

No-license-cost systems focused on logs and search

OpenSearch

OpenSearch is an Apache 2.0 search and analytics project with a storage engine, OpenSearch Dashboards, security, alerting, and observability plugins. The project's official FAQ confirms that all OpenSearch project software is released under Apache 2.0. It is a strong foundation for indexed log search, field filters, dashboards, and custom data models, but it is not a turnkey Datadog replacement.

Current OpenSearch observability uses more than the search cluster. Data Prepper receives, filters, transforms, and routes telemetry. Its unified OTLP source accepts logs, metrics, and traces over gRPC or HTTP with documented encoding constraints. OpenSearch's current APM architecture stores logs and traces in OpenSearch while routing metrics to Prometheus. That is an assembled stack, not automatic three-signal parity.

The operational budget includes JVM and shard sizing, mappings, index templates, rollover, retention policies, cluster upgrades, snapshots, restore testing, and query isolation. Search flexibility can become expensive when every field is indexed or mappings drift.

OpenSearch documents two first-party MCP paths. The open-source OpenSearch MCP Server runs beside the cluster and works with self-managed OpenSearch, Amazon OpenSearch Service, and Serverless. It supports basic authentication, AWS IAM or profile credentials, headers, and mTLS; anonymous access is possible but should not expose production data. Core search and cluster tools are enabled by default. Optional catalogs add operations such as creating and deleting search configurations, query sets, judgments, and experiments. The cluster identity and its index or API permissions remain the authorization boundary.

OpenSearch 3.3 also introduced a separate in-cluster Streamable HTTP MCP endpoint. An administrator must enable it and register the tools clients may discover. Treat tool registration as catalog configuration, not as a substitute for OpenSearch Security roles, network controls, and least-privilege index access.

OpenSearch fits teams whose main Datadog workload is log analytics and whose platform engineers already understand search clusters. It is less attractive when a small team wants a single managed incident workflow with minimal assembly.

Graylog Open

Graylog Open is a self-managed centralized log platform rather than a full observability suite. Graylog's current product page describes log collection, search, dashboards, pipelines, events, and alerts without a license charge. It is useful when Datadog Logs is the target and metrics, tracing, browser monitoring, and APM will remain elsewhere.

License wording matters. Graylog Open uses the Server Side Public License. Graylog's licensing explanation states that SSPL is not OSI-approved and adds obligations for offering Graylog as a service. That makes Graylog Open a no-license-cost, source-available option, not an OSI open-source one. Review the license for hosted or managed-service use.

The product provides a more curated log workflow than a raw search engine, but the operator still owns Graylog, its data tier, storage sizing, retention, backups, upgrades, pipeline behavior, and collector inputs. Some packaged content, governance, compliance, security, and support capabilities belong to paid editions; compare the current feature matrix against access and retention needs.

Graylog Open now includes native MCP support. The current setup guide labels it experimental, requires Graylog 7.0 or later, and keeps remote MCP disabled until an administrator enables it. A client authenticates to /api/mcp with a Graylog API token over Basic authentication, and the token's user roles govern the same REST permissions used by the tools. Graylog warns that permitted actions may modify live data or trigger events and advises a dedicated read-only user, controlled non-production use, and one connected Graylog instance at a time.

Hosted allowances with less platform work

Grafana Cloud Free

Grafana Cloud Free is a hosted allowance rather than self-hosted open-source software. Grafana's current plan guide describes the Free plan as having lower usage limits, shorter retention, and community support; paid plans increase those boundaries. It covers managed metrics, logs, traces, dashboards, and alerts, so it can validate an OpenTelemetry or Grafana-centered architecture without first operating every backend.

The UI and query models match the Grafana ecosystem: dashboards, Explore, Logs Drilldown, PromQL, LogQL, and TraceQL. The main constraint is not feature count but the workload that fits within current ingest, retention, and user limits. Confirm those limits in the current plan before routing production telemetry, and define what happens when the allowance is reached.

Grafana Cloud's hosted MCP server is part of Grafana Assistant. The current MCP documentation requires Assistant availability, accepted terms, an MCP access role, and OAuth 2.1. Access is user-scoped through Grafana RBAC. Consent separates Read, Query, and Write, but Query can execute raw SQL that may modify data; remove both Query and Write for a strictly read-only connection. The service is Cloud-only, uses Streamable HTTP, and counts connected users against Assistant usage, with hard active-user limits on the Free plan.

Grafana Cloud Free fits a small or bounded workload that benefits from managed operations. It is not a promise that production ingest, retention, governance, or agent use will remain inside the hosted allowance.

New Relic Free

New Relic Free is a hosted, broad-observability option. The current plan page includes application performance, traces, logs, infrastructure monitoring, dashboards, queries, and alerts, with limits on data ingest, retention, and full-platform users. Those limits can make it useful for a small service or evaluation environment without turning it into an unlimited production replacement.

New Relic uses a unified data platform and NRQL for queries across its telemetry model. This reduces the assembly required by a component stack, but instrumentation, ingest controls, attribute design, alert migration, and access roles still need deliberate work. Verify the current limit behavior before cutover: a hosted allowance can stop accepting data or require an upgrade when usage exceeds its boundary.

New Relic's Ground Truth MCP overview says MCP is available to all accounts: data and CCU users receive core tools, while aCCU users receive all tools, including advanced tools. An organization role must grant MCP read permission, and Feature Control Manager separately controls the server, local clients, API-key access, integrations, and non-GA Preview tools.

MCP setup recommends OAuth and documents separate US, EU, and Japan endpoints. User API keys support only a subset; several AI analysis and Preview tools are OAuth-only. The current catalog is primarily read and query oriented, including entity lookup, NRQL, recent logs, alert listings, and analysis. The include-tags header narrows what is shown to the model but is not the authorization boundary; New Relic RBAC and the MCP organization permission are.

New Relic Free fits teams that value a managed, integrated interface and can keep the selected workload within the current limits. It does not provide the deployment control of a self-hosted stack.

Account for costs that do not appear on a license page

Self-hosted software moves spend rather than eliminating it. Estimate at least these categories:

• Collector, ingestion, query, and background-processing compute.
• Hot storage, object storage, indexes, replicas, snapshots, and cross-region copies.
• Network transfer between clusters, regions, and storage services.
• High-availability capacity and a tested recovery environment.
• Security updates, dependency upgrades, identity integration, and audit evidence.
• On-call time for queue backlogs, failed compaction, index pressure, corrupt state, and version migrations.
• Engineering time to recreate dashboards, queries, monitors, service catalogs, and runbooks.

Hosted allowances remove much of the backend maintenance but introduce ceilings. Model what happens at the boundary: data stops, retention shortens, users lose access, or paid usage begins. Do not rely on a marketing label when the account's actual plan and usage page can be checked.

Migrate without creating an observability blind spot

1. Inventory current coverage. List every Datadog signal, agent, integration, dashboard, alert, SLO, archive, access rule, API client, and incident dependency. Mark what must move and what can be retired.
2. Normalize collection. Use OpenTelemetry where it is supported, but confirm every receiver, processor, exporter, retry queue, and resource attribute. OpenTelemetry improves portability; it does not translate proprietary dashboards or query languages.
3. Dual-send a bounded workload. Route one representative service to both systems. Compare event counts, timestamps, cardinality, trace completeness, log fields, metric types, and alert timing. Set an end date so dual ingest does not become permanent cost.
4. Rebuild investigation paths. Recreate the exact queries responders use: release regression, failing endpoint, pod restart, slow dependency, customer error, and security event. A dashboard screenshot is not evidence that raw search works.
5. Test retention and recovery. Verify rollover, deletion, archive access, backups, and a real restore. For hosted allowances, verify what happens when the limit is approached or exceeded.
6. Recreate access boundaries. Test least-privilege roles with real users, API tokens, and service accounts. Repeat the test for MCP or other agents; hiding a tool from the model does not revoke its backend permission.
7. Run both alert paths. Trigger known conditions and compare missing data, grouping, notification routing, acknowledgment, and recovery. Remove the old alert only after the new path has been observed end to end.
8. Measure the new total cost. Include infrastructure, storage, transfer, support, and monthly engineering hours. Review it again after production volume and retention have stabilized.

Direct answers before choosing

Which option comes closest to full-stack Datadog coverage?

SigNoz Community and OpenObserve package logs, metrics, and traces into one self-hosted product. The Grafana OSS ecosystem can cover the same signal categories through separate components. New Relic Free and Grafana Cloud Free provide hosted multi-signal allowances. None should be treated as exact feature parity; validate the specific APM, alerting, browser, security, and governance workflows in use.

Is Prometheus alone a free Datadog alternative?

Prometheus replaces a metrics collection, query, and alerting layer. It does not store application logs or distributed traces. Pair it with a log backend, a trace backend, a UI, and collectors when those signals matter.

Are OpenSearch and Graylog complete observability replacements?

Not by themselves. Both are defensible for centralized logs and search. OpenSearch can participate in a wider OpenTelemetry and Prometheus architecture, while Graylog remains focused on log management. Keep or add separate metrics, tracing, APM, and user-experience tools as required.

Does open source remove vendor lock-in?

It removes some license and hosting constraints, not every dependency. Query languages, schemas, dashboards, index layouts, storage engines, and operational knowledge can still create switching costs. Portable collection and documented field conventions reduce that risk.

Can an AI agent investigate a no-cost observability stack safely?

Only when its credentials, data scope, and write permissions are explicit. Grafana OSS can use service-account RBAC. SigNoz self-hosted MCP uses a service-account API key and has write tools. OpenObserve OSS MCP gives the connected account broad organization privileges and includes destructive tools. OpenSearch optional MCP catalogs and Graylog's experimental MCP include mutations. New Relic core access is broadly available, while advanced and Preview tools have separate entitlement and feature controls. In every case, use a separate identity, limit network reach, audit calls, and require human confirmation for mutations.

If the real requirement becomes a paid logs-focused service rather than a full Datadog replacement, Fluxtail provides named streams, a modern Live Tail, documented search and filters, alerts, a separate built-in AI chat, and an account-bound hosted MCP server using OAuth with PKCE. Review Fluxtail pricing or create an account when that narrower operating model fits.