Datadog vs Grafana - Where Self-Hosting and Cloud Break Even

Grafana OSS, Grafana Cloud, and Datadog Are Not on the Same Footing

The biggest reason Datadog-versus-Grafana comparisons fail to connect is that "Grafana" refers to two different things. One is the open-source Grafana you install and run on your own servers, used as a visualization tool layered on top of data sources such as Prometheus. The other is Grafana Cloud, the SaaS operated by Grafana Labs, a usage-based service that includes the storage backend for metrics, logs, and traces. Datadog is a SaaS of the same kind as the latter, but it differs in that its billing unit is a stack of per-host pricing plus usage.

Grafana Labs announced on April 20, 2021 that it was moving the licenses of Grafana, Loki, and Tempo from Apache License 2.0 to AGPLv3, and self-hosted use itself remains free (Source: Licensing, cited above). In other words, the comparison is not "free vs paid" but a three-way choice between paying with people, paying by usage, or paying per host. The three choices are laid out below using only the billing mechanics and feature facts written in both vendors' official documentation. This article explains how billing works. For current unit prices and plans, refer to each vendor's official pricing page.

The Difference in Billing Models - Usage by Series Count and GB, or a Stack of Per-Host Prices

Grafana Cloud's pricing has three tiers: a free tier called Free; Pro, where a monthly base fee includes a fixed volume of series, logs, and users and anything above that is billed by usage; and Enterprise, contracted on an annual commitment. Pro usage is counted in three units, active series for metrics, GB ingested for logs, and active users for people, and each of them follows a banded structure in which the unit price steps down as volume grows. Retention is 13 months for metrics and 30 days for logs and traces (as of September 2026, Source: Grafana Pricing). Datadog's Infrastructure Monitoring Pro is a monthly per-host price that includes a per-host allotment of custom metrics and 15 months of metric retention, while logs are a two-part structure of a per-GB ingestion price plus a per-indexed-event price that varies with the retention period (Source: Datadog Pricing). The per-host price may differ depending on the contract form (annual or monthly).

The most important row in the table is "Metrics unit". Grafana Cloud scales with cardinality (the number of series) and does not care how many hosts you have. Datadog scales with the number of hosts and does not care about the number of series as long as it stays within the allotment. Which one is cheaper for the same environment is determined by "how many series each host emits", and that is the conclusion of this table. The stacking structure of the pricing itself is covered in How to Decode the Pricing Structure.

The Hidden Cost of Self-Hosting - The People Who Keep Prometheus + Grafana Running

"Grafana is free" holds only when there is a Prometheus running behind the visualization and someone responsible for operating it. The official Prometheus documentation describes its design as "not relying on distributed storage, with a single server node that operates autonomously" and "collecting time series via a pull model over HTTP", and while it prioritizes the reliability you can lean on precisely during an outage, it explicitly states that it is "not suited to use cases that require 100% accuracy, such as per-request billing" (as of September 2026, Source: Prometheus Overview). A design in which a single server operates autonomously means, conversely, that "you design long-term retention and high availability yourself". This is where the people cost comes in.

This is the kind of work where you cannot say in advance how many hours per month it will take, and if a single person is responsible, the whole monitoring platform becomes dependent on that one person when they leave or transfer. What Grafana Cloud is selling as "base fee + usage" is precisely the price of taking these five items off your hands. Datadog is the same: the per-host price includes 15 months of retention and availability. Therefore the correct way to estimate self-hosting is not "server cost" but "hours per month of the monitoring platform owner multiplied by their hourly rate"; if that figure exceeds the SaaS fees of either vendor, self-hosting is the more expensive option, and if it falls below, self-hosting is cheaper. This reversal is structurally most likely to occur at the scale of a few dozen hosts, where you cannot assign a dedicated monitoring owner.

Where Grafana Wins: Free OSS, Visualization Freedom, and Reuse of Prometheus Assets

Even in an article that takes Datadog's side, this part is written honestly. First, the cost floor is different. Grafana OSS is AGPLv3 and free to use, and Grafana Cloud's Free tier is also free of charge, with no billing as long as you stay within a fixed volume of active series and logs at 14 days of retention (as of September 2026, Source: Grafana Pricing). Datadog's Free tier has a cap on host count and only 1-day metric retention (as of August 2026, Source: Datadog Pricing), so at the stage of "I want to look at two weeks of graphs for free", Grafana Cloud Free goes further. Next is visualization freedom. Grafana is designed to place multiple data sources on a single dashboard, including Prometheus, Loki, various databases, and Datadog itself, and Grafana Labs publishes a data source plugin that queries Datadog metrics from Grafana and visualizes them (as of September 2026, Source: Datadog data source for Grafana). For requirements like fine-tuning every detail of how a dashboard looks, or consolidating several in-house monitoring tools onto one screen, Grafana is the better fit. Finally, existing assets. For an organization that already has Prometheus exporters and PromQL alert rules in place, Grafana Cloud is an option that lets you bring those assets over just by changing the destination, whereas moving to Datadog means rewriting the PromQL alert rules. The metrics emitted by the exporters themselves can be ingested through the OpenMetrics integration (as of September 2026, Source: OpenMetrics). These three points, the cost floor, visualization freedom, and reuse of Prometheus assets, are structural differences that will not reverse no matter how many features Datadog adds.

Where Datadog Pays Off: When You Want One Agent to Cover Everything from Collection to Alerts

Datadog's strength is not the superiority of individual features but the fact that collection, visualization, alerting, and correlation are all complete within one product. Installing the Datadog Agent gives you more than 50 host metrics by default, more than 1,000 integrations to extend coverage, and tags attached to the Agent are carried on every metric, log, and trace (as of September 2026, Source: Why should I install the Datadog Agent on my cloud instances?). To reach the same state with Prometheus + Grafana, you have to select and deploy exporters, configure scraping, design labels, and wire up Alertmanager yourself. This difference matters under the following three conditions. First, incident investigation does not end with metrics. An investigation that goes from "CPU spiked" to "the logs at that moment" to "the slow requests at that moment" with the same tags takes fewer steps in Datadog, where Dashboards, logs, and traces sit on a single data model. Second, the monitored footprint keeps growing. Per-host billing lets anyone estimate "one more host means one more host's worth of the unit price", whereas series-based billing makes it hard to predict in advance how many series a new service will emit, and in organizations unfamiliar with custom metrics design, the bill becomes unpredictable. Third, you cannot assign a dedicated monitoring owner. Even among SaaS products, Datadog is designed to look after the collection side (the Agent) as well, so you never have to worry about Prometheus availability or exporter versions, making it the configuration with the lowest operational burden. Conversely, in an organization where investigations are metrics-centric, targets are fixed, and a dedicated monitoring owner exists, the conclusion is that the Grafana family is cheaper and more flexible. Having acknowledged that, in an organization where all three conditions, cross-cutting investigation, growth, and a small team, are present, the economics of Datadog's per-host price become visible when you think of it as buying "one monitoring platform operator".

The Variable That Decides the Trade-Off Is Not the Host Count but the Series per Host

Instead of lining up both vendors' unit prices and producing amounts, let us sort out which variables move the bill. Grafana Cloud Pro's metrics cost is determined by "base fee + (active series − series included in the base fee) × the per-band series price", and the number of hosts does not appear in the formula (as of September 2026, Source: Grafana Pricing). Datadog's Infrastructure Monitoring Pro is determined by "host count × per-host price", and as long as custom metrics stay within the allotment, the series count does not appear in the formula (Source: Datadog Pricing). In other words, when both are placed in the same environment, what moves Grafana Cloud's bill is the series count and what moves Datadog's bill is the host count, so which one is cheaper is decided by a single ratio: "how many series each host emits". In an environment where this ratio is small, that is, each host emits few series, adding hosts increases Grafana Cloud's bill only gradually. In an environment where the ratio is large, that is, containers and application-specific indicators make each host emit many series, Datadog's per-host price comes out cheaper already at a small number of hosts.

The conclusion of the table is that the dividing line is not the number of hosts but the number of series per host. High-cardinality environments, with many containers, rich tag combinations, or many application-specific indicators, lean toward Datadog, while plain environments in which a single host emits only a handful of series lean toward Grafana Cloud. To judge your own environment, if you run Prometheus, simply divide the current number of active series by the number of hosts to get the ratio. According to the official FAQ, Grafana Cloud's series billing is determined by two factors, active series and data points per minute (same source), so it is also worth remembering that shortening the send interval increases the bill even with the same number of series. Touching on the line items left out of the table: Grafana Cloud has per-user billing per active user, while Datadog has no per-user billing. In an organization where dozens of people look at dashboards, add this difference to your judgment as well.

The Practical Answer of Running Both, and What to Check Before Deciding to Switch

In practice it often does not come down to an either-or choice, and there are two officially documented paths to running both. One is the data source plugin that queries Datadog metrics from the Grafana side, which lets you place Datadog data alongside your existing Grafana dashboards while keeping them intact (as of September 2026, Source: Datadog data source for Grafana). The other is the Grafana integration on the Datadog side, which collects the Grafana server's own internal metrics as an Agent check so that Grafana's health can be monitored in Datadog (Source: Grafana Integration). The former "keeps the place you look at in Grafana", the latter "adds Grafana to the monitored targets"; they are different uses, so do not confuse them. Narrowing down to four items to verify before deciding to switch or run both:

Of the four items, 1 and 3 can be obtained as numbers, so start there. If 1 is around 1,000 and 3 is small, the decision to stay on Grafana is rational. If 1 is large, 2 is "descends", and 3 cannot be predicted, Datadog's per-host price functions as insurance worth one operator. The steps after deciding to adopt are summarized in the Adoption Checklist, and the overall picture of pricing in How to Decode the Pricing Structure.