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Why Datadog Falls Short for Log Management and What to Do Instead

4 MIN READ
4 MIN READ
Rishin Pandit

6.4.25

4 MIN READ
4 MIN READ

Datadog may be the default choice for all-in-one observability, but its logging experience takes a back seat to the broader platform. Logs are primarily designed to feed into metrics and traces, which leads to tradeoffs such as slower search, complex workflows, and a UI that isn’t optimized for log investigations. As a result, Datadog doesn’t align with how developers actually troubleshoot.

Mezmo takes a different approach. Purpose-built for logs, it gives engineers a faster, cleaner, and more focused way to find answers. From the ground up, Mezmo was designed to make logs easy to search, manage, and route without forcing teams into a heavyweight observability suite. Unlike Datadog, which added logs after the fact, Mezmo treats logs as first-class data. Every part of the experience, from ingestion to analysis, is optimized for fast and intuitive access to the information that matters.

A Focused Approach to Log Management 

Mezmo’s Platform (Log Analysis + Telemetry Pipelines) is designed for fast, efficient troubleshooting. With fewer tabs, fewer clicks, and no complex query language, engineers can jump straight into investigations without friction as soon as their logs are received. No digging through layers of interface just to find what matters. That means faster incident response, lower MTTR, and fewer late-night firefights.

Logs are automatically parsed at ingest, with fields extracted from JSON, key-value pairs, and other standard formats. These fields are indexed instantly and ready to search, filter, and alert on without custom configuration. Even unstructured logs are cleanly ingested, with full regex support and out-of-the-box templates that simplify setup from a single point of control.

One of the most loved features across Mezmo is live tail—a real-time, searchable, filterable view of logs from all your services and environments, streaming in as they arrive, even at high volume. With live tail, logs are automatically parsed at ingest, so fields are extracted and immediately available for filtering and searching without any extra configuration. You can filter and search the stream in real-time without pausing or switching contexts. There’s no delay, no buffering, and no session limits. Whether you're monitoring a deployment or diagnosing a regression, live tail delivers uninterrupted visibility and immediate insight.

Whether you’re monitoring a deployment or diagnosing a regression, live tail provides continuous visibility and insights. When you need to dig deeper, you can pivot into historical data without losing your place. Mezmo keeps live tail fully integrated and always accessible. It's one continuous interface built for speed, awareness, and decisive action.

It’s Your Data – You Should Control It (and the Costs)

Having a pipeline integrated with your logging tool gives the power to shape your data before it reaches storage, if it even needs to be stored. With Mezmo, you can enrich, restructure, and normalize logs upstream so they are consistent, readable, and ready for analysis. This leads to cleaner dashboards, simpler queries, and faster investigations.

A key part of this experience is Mezmo’s data profiler,  which inspects log data in motion to surface key fields, detect patterns, and highlight inconsistencies, even in high-volume, unstructured sources. This real-time visibility helps developers make smarter decisions about what to parse, how to route data, and what to drop.

Fine-grained volume control helps ensure your logs don’t become a cost burden or a source of distraction. As one engineering leader at an enterprise social media company put it: “I actually think you should try to throw away 50 percent of the data before you even ingest it… so much of it is garbage.” Mezmo helps you cut through that noise.

With responsive pipelines, Mezmo gives you dynamic control over log volume, adjusting behavior in real time based on your environment. You can automatically trigger full-fidelity capture during incidents, apply stricter filtering during traffic spikes, and return to normal processing when conditions stabilize. This automated control helps ensure you send the right data at the right time, reducing noise and costs. 

You can drop noisy logs, sample less critical ones, and combine repetitive patterns into summaries before they increase your bill or add clutter. This results in logging that keeps your systems manageable and lets your team focus on the data that matters.

Flexibility Without Lock-In

We understand that Mezmo won’t always be the final destination for every log. That’s why our platform isn’t designed to lock in your telemetry data. It’s built to move and evolve with your team. Teams need the flexibility to choose observability tools that best fit their needs. Security logs might belong in Splunk, metrics could be routed to Prometheus for low-cost monitoring, and application logs may be better suited for a dedicated logging provider.

You can test new tools, split traffic across multiple destinations, or adapt your observability stack over time without paying extra to forward logs. Mezmo integrates with providers like Datadog, New Relic, or any OpenTelemetry-supported destination, giving you the freedom to use the right tool for the job.

If logging is central to how your team investigates issues, it makes sense to choose a tool built specifically for it. Datadog’s log experience may be adequate as part of a larger platform, but it brings tradeoffs in speed, simplicity, flexibility, and cost. Mezmo takes a different approach. It is faster to search, easier to use, and flexible enough to support your evolving stack. For teams that need high-performance logging and full control over their data, Mezmo offers a faster, leaner, and more sustainable path forward.

Learn how to optimize your Datadog costs with Mezmo and get started with a 30-day free trial.

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