SigNoz vs Grafana
Under the hood, Grafana is powered by multiple tools like Loki, Tempo, Mimir & Prometheus. SigNoz is powered by a single columnar datastore to serve logs, metrics, and traces in a single pane of glass from Day 1, which enables better context for troubleshooting performance issues.
Why do Engineering Teams Choose SigNoz over Grafana?
SigNoz is loved by developers. With over 20,000+ Github stars, it's one of the top projects in the observability domain. We have helped many of our users to make the switch from Grafana.
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 powered by a single columnar datastore, ClickHouse. Ingestion, storage, and querying of signals are optimized for ease of use and intelligent out-of-box correlation between the three signals.
For open-source and self-hosted users of SigNoz, there is less operational overhead and a better developer experience because of using a single data store.
True OpenTelemetry(OTel)-native solution
SigNoz is built from the ground up for OpenTelemetry. That means OTel-first docs, visualizations, & features are meant to truly take advantage of OpenTelemetry's potential.
Grafana Cloud also uses OpenTelemetry for application observability but uses different databases for each signal - Loki for logs, Tempo for traces and Prometheus for metrics.
SigNoz uses columnar database for faster ingestion & aggregation
SigNoz uses ClickHouse - a fast open-source distributed columnar database for all three types of signals - logs, metrics, and traces. It was built to do analytical queries like `Group By` fast. Read more on what makes ClickHouse so fast →
Ingestion and aggregations are lightning-fast while providing best-in-class compression for economical storage.
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 open-source SigNoz with Elasticsearch and Loki. Our key findings for Loki showed:
- Ingestion is mainly limited by the number of streams that it can handle.
- Loki was not able to return the results of our test queries.
- 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.
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.
Product Comparison
| Feature | SigNoz | Grafana | Remarks |
|---|---|---|---|
| Self-Host | Yes | Limited | For Grafana, you need to manage multiple backends if you opt for self-host which is a lot of operational overhead. |
| APM metrics to logs & traces | Yes | Yes | You can jump from APM metrics to logs & traces. |
| Traces to logs | Yes | Yes | You can jump from traces to associated logs to get more context while troubleshooting. |
| No User-based Pricing | Yes | No | Grafana charges $20 per active IRM user. (Source) |
| Aggregation on span attributes | Yes | No | SigNoz allows you create aggregations on span attributes. For example, find the p99 latency on any span attribute. |
| Aggregation on Log attributes | Yes | No | SigNoz allows you create aggregations on log attributes as well. |
| Alerts on complex aggregations | Yes | No | Create complex aggregates, add them to dashboards and create alerts to monitor discrepancies. |
| Automatic exceptions from OTel trace data | Yes | No | SigNoz provides a dedicated Exceptions tab that automatically lists down all exceptions captured automatically from an OTel instrumented application. |
| OTel-native Messaging Queue Monitoring | Yes | No | Leveraging OTel's trace context propagation & semantic conventions, SigNoz provides end-to-end observability of messaging queues like Kafka & Celery. |
Better Value for Money
We did a pricing comparison of SigNoz with other popularity observability tools including Grafana. SigNoz can save up to 45% of your Grafana bill.
