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Maple vs Datadog

Datadog is powerful but comes with complex per-host pricing and proprietary agents. Maple delivers the same distributed tracing, logs, and metrics with transparent usage-based pricing, native OpenTelemetry support, and zero vendor lock-in.

5 min
Setup time

From zero to ingesting traces, logs, and metrics with OpenTelemetry

100%
Open source

Every line of code is open — audit, contribute, and self-host freely

$0
Per-seat cost

Unlimited team members included. No per-seat pricing, ever

Feature Maple Datadog
Core Observability
Distributed tracing
Log management
Metrics & dashboards
Custom dashboards
Alerting
Platform & Architecture
OpenTelemetry native
Open source
Self-hosting available
No vendor lock-in
AI / MCP integration
API-first design
Pricing & Access
Pricing model
Usage-based, transparent
Complex per-host + per-GB
Team seats included
Unlimited
Per-seat pricing
Setup time
Minutes
Hours to days
Proprietary agents required
Data retention control
Common challenges

Problems with Datadog that Maple solves

Datadog

Unpredictable billing that spikes with traffic

Maple

Transparent usage-based pricing — you always know what you'll pay before you scale.

Datadog

Proprietary agent lock-in ties your instrumentation to one vendor

Maple

100% OpenTelemetry native. Your instrumentation is portable and vendor-neutral.

Datadog

Complex pricing tiers across hosts, containers, custom metrics, and log volume

Maple

One simple pricing model based on data volume. No per-host fees, no hidden surcharges.

Datadog

No option to self-host or keep data within your own infrastructure

Maple

Self-host Maple on your own infrastructure for full data sovereignty and compliance.

Why choose Maple

Key advantages over Datadog

Transparent pricing

Simple usage-based pricing with no per-host fees, no hidden costs, and no surprise bills at the end of the month.

OpenTelemetry native

Built from the ground up on OpenTelemetry standards. No proprietary agents to install or maintain — use the instrumentation you already have.

AI & MCP integration

Diagnose issues faster with AI-powered root cause analysis and MCP tool integration for automated observability workflows.

Open source

Inspect every line of code, contribute features, and trust that your observability platform has no black boxes.

No vendor lock-in

Your data stays in open formats. Switch providers or self-host at any time — your instrumentation never needs to change.

Self-hosting available

Run Maple on your own infrastructure for complete data sovereignty, compliance, and cost control.

Migration

Switch from Datadog in minutes

01

Keep your existing OTel instrumentation

If you already use OpenTelemetry SDKs alongside the Datadog agent, just point the OTLP exporter to Maple. No code changes needed for OTel-instrumented services.

02

Replace the Datadog agent with the OTel Collector

Swap the proprietary Datadog agent for the open-source OpenTelemetry Collector. Configure it to export to Maple's OTLP endpoint.

03

Rebuild dashboards and alerts in Maple

Use Maple's dashboard builder and alerting system to recreate your monitoring views. AI-assisted setup helps you get started faster.

Pricing

Estimated monthly cost: Maple vs Datadog

Drag the sliders to match your usage and see how the costs compare.

Adjust your usage
15 hosts
10 hosts
100 GB/mo
10 users
MapleRecommended
$39/mo
Startup plan$39
Team seatsFree
300 GB included
Unlimited — always free
Datadog
$571/mo
Infrastructure$225
APM$310
Log management$36
15 hosts × $15
10 hosts × $31
100 GB ingested + indexing
Save $532/month

That's 93% less than Datadog — or $6.4k/year back in your budget.

Start free trial

Estimates based on published pricing as of 2025. Actual costs may vary based on contract terms, volume discounts, and additional features. Maple pricing based on the Startup plan ($29/mo with 300 GB total included data).

FAQ

Frequently asked questions

Is Maple a drop-in replacement for Datadog?
Maple covers the core observability features most teams use: distributed tracing, log management, metrics dashboards, alerting, and AI-powered diagnostics. If your workflow centers on traces, logs, and metrics, Maple can replace Datadog for those use cases. Some advanced Datadog-specific features like Synthetic Monitoring or Network Performance Monitoring are not yet available.
How does Maple's pricing compare to Datadog?
Maple uses transparent, usage-based pricing based on data volume — no per-host fees, no per-seat charges, no separate costs for custom metrics. Datadog's pricing combines per-host, per-GB, and per-feature charges that can lead to unexpected bills as you scale. Most teams see significant cost savings with Maple.
Can I migrate from Datadog to Maple without downtime?
Yes. You can run Maple alongside Datadog during migration by dual-shipping your telemetry data. Point your OpenTelemetry Collector at both backends, verify your data in Maple, then cut over when ready.
Does Maple support the Datadog agent?
Maple does not use proprietary agents. Instead, it's built on OpenTelemetry — the open standard for observability. You'll replace the Datadog agent with the open-source OpenTelemetry Collector, which gives you vendor-neutral instrumentation that works with any OTel-compatible backend.
Can I self-host Maple instead of using the cloud version?
Yes. Maple's source is available under FSL-1.1 and can be self-hosted on your own infrastructure. This gives you complete control over your data, compliance with data residency requirements, and eliminates ongoing SaaS costs.
Does Maple have AI-powered features like Datadog?
Maple includes AI-powered diagnostics and an MCP (Model Context Protocol) integration that lets AI agents query your observability data directly. This enables automated root cause analysis, anomaly detection, and conversational debugging workflows that go beyond traditional dashboards.
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