SigNoz VS Grafana

In-Depth: SigNoz vs Grafana

Under the hood, Grafana is powered by multiple tools like Loki, Tempo, Mimir & Prometheus. SigNoz is built as a single tool to serve logs, metrics, and traces in a single pane of glass from Day 1.

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Key Points: SigNoz vs Grafana

Why do devs choose SigNoz over Grafana?

SigNoz is loved by developers. With over 14k+ Github stars, 100+ contributors, and 20k+ community members, it’s one of the top open source projects in the observability domain. Many of our users have switched from Grafana.

Here are a few reasons why.

1. SigNoz is built as a single application to serve logs, metrics, and traces.

Grafana started as a data visualization tool. It slowly evolved into a tool that can take data from multiple data sources for visualization.

For observability, Grafana offers the LGTM stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics). You need to configure and maintain multiple configurations for a full-stack observability setup.

SigNoz is a single application that provides logs, metrics and traces under a single pane of glass. Ingestion, storage, and querying of signals are optimized for ease of use and intelligent out-of-box correlation between the three signals. There is less operational overhead and better developer experience with SigNoz.

2. SigNoz is OpenTelemetry-native

OpenTelemetry is the second most active project in the CNCF, with only Kubernetes being more active. Using an open source standard like OpenTelemetry for generating telemetry signals frees you from vendor lock-in. SigNoz is built to support OpenTelemetry from Day 1.

We provide features like application exceptions to traces from OTel data for fast debugging. Grafana also supports OpenTelemetry. But it uses different backends for different signals - Loki for logs and Tempo for traces.

3. SigNoz uses columnar database for faster ingestion & aggregation

SigNoz uses ClickHouse - a fast open source distributed columnar database. Ingestion and aggregations are lightning-fast while providing best-in-class compression for economical storage. It was built to do analytical queries like Group By fast. Read more on what makes ClickHouse so fast.

4. Loki was not built to index and query high-cardinality data

Loki doesn’t perform well if you want to index and query high-cardinality data.

“As a Loki user or operator, your goal should be to use the fewest labels possible to store your logs. (Source: Grafana)”

We did a logs performance benchmark of SigNoz with Elasticsearch and Loki. Below are our key findings for Loki for ingestion, querying, and storage:

Ingestion is mostly limited by the number of streams that it can handle.
For our test queries, Loki was not able to return the results.
Loki took the least amount of storage as it indexed only two keys.

SigNoz is able to perform fast aggregation queries and also has efficient resource utilization during ingestion.

5. SigNoz is much easier to self-host

If you want a self-hosted solution, SigNoz is a better choice. Since Grafana has multiple backends for different telemetry signals, it’s difficult to manage. With SigNoz, you only need to manage a single backend for a full-stack observability setup. We also provide managed self-host services.