You need both.
Lighthouse does both.
Soda specializes in data quality. Lighthouse covers business metric monitoring and data quality checks — in one tool, no code required, accessible to your whole team.
How Lighthouse covers data quality
Every data quality check is a SQL query on a schedule. The trick is writing it once for allyour tables — using your warehouse metadata or your own audit table as the source, and Lighthouse's segment feature to fan out one metric into per-table alerts.
Query your warehouse metadata once. Segment by table_name — Lighthouse fires a separate alert per table that goes stale.
table_namePull row counts from your warehouse metadata. Lighthouse compares each table to its own 7-day baseline automatically.
table_nameWrite a stats view once that calculates null rates per column. Segment by column_name — one alert per column that spikes.
column_nameMaintain a dedup stats view or query your audit table. Segment by table — Lighthouse alerts per table when duplicates appear.
table_nameQuery your pipeline log table. Segment by pipeline_name — one metric covers your entire ETL stack, one alert per job that runs late.
pipeline_nameStore daily aggregates in a stats table. Segment by metric_name — Lighthouse monitors all of them and alerts on any anomalous value.
metric_nameWorks across Snowflake, BigQuery, Postgres, and MS SQL Server — each with dialect-correct SQL.
Side by side
Where each tool wins — and where the honest tradeoffs are.
Lighthouse
Soda
When to choose which
An honest guide. Both tools are good — the right answer depends on your situation.
Choose Lighthouse when…
- You need business metric monitoring alongside data quality — revenue, users, conversions, product KPIs
- You have analysts or business stakeholders who need to manage their own metrics without code
- Setup speed matters — you want alerts running in minutes, not a YAML project to maintain
- You want one tool and one bill instead of two specialized platforms
- Alert noise is a problem — you need adaptive baselines, not manual threshold tuning
Choose Soda when…
- Your primary need is automated data quality across a large number of tables with minimal configuration
- Your team is all-technical and code-based workflows (YAML, CLI, dbt, Airflow) are the norm
- You need deep pipeline integration — checks that run inside your Airflow or Dagster jobs
- Schema drift detection and automated column-level profiling are must-haves out of the box
Where Soda genuinely has more depth
Soda's automated observability is more comprehensive out of the box — and it works across more connectors. It can detect schema drift, column-level anomalies, and pipeline freshness across hundreds of tables with minimal configuration, whether you're on Snowflake, Redshift, Databricks, or other engines. If automated zero-config data quality across your entire data platform is the primary requirement, Soda has more coverage today.
Lighthouse currently supports Snowflake, BigQuery, Postgres, and MS SQL Server. You write the SQL for each custom quality check — a one-time effort, not an ongoing project. Pre-built quality packs for more connectors are on the roadmap.
The tradeoff: most Soda checks are written in SodaCL YAML — meaning every check goes through an engineer, unless you're on the $750/mo Team plan. And business metric monitoring isn't in scope. If your team includes non-technical users, or if KPI alerting matters too, that's a real constraint.
What Lighthouse brings to the table
The things Soda doesn't do — or makes significantly harder.
Business metrics and data quality in one place
Revenue drops, user activity spikes, and pipeline freshness failures all live in the same alert feed. One tool to configure, one Slack integration, one system your team actually checks.
Non-technical users can self-serve — on every plan
Any analyst on your team can create and manage their own metrics using the visual builder — no code, no YAML, no engineering ticket. Free tier included.
Visual builder + raw SQL — no forced choice
Simple business metrics use the visual builder. Advanced or custom quality checks use raw SQL. Both go through the same scheduling, alerting, and audit system.
Adaptive alerting that learns your patterns
Snoozing, consecutive-trigger gating, and trend-based thresholds mean alerts fire when something genuinely changed — not every time the metric wavers slightly.
Full audit trail and workflow
Every run is logged — values, SQL, who acknowledged what. Severity levels, ownership, and access controls per metric. Your team can act on alerts, not just receive them.
Transparent pricing, generous free tier
Start for free with up to 5 metrics. Upgrade when you need more. No enterprise contract required to access the UI or onboard non-technical team members.
Common questions
Can Lighthouse actually do data quality monitoring?
Yes. Lighthouse runs any SQL query against your warehouse on a schedule and alerts when a threshold is crossed. That means freshness checks, null rate monitoring, volume anomalies, duplicate detection — all of it. You write the SQL once, Lighthouse monitors continuously.
Where does Soda have an edge?
Soda's automated observability is more comprehensive out of the box — it can detect schema drift, column-level anomalies, and pipeline freshness across hundreds of tables with minimal configuration, and it supports more connectors. If zero-config data quality across your entire platform is the primary requirement, Soda has more coverage today.
My team needs both data quality and business metrics. Is Lighthouse the right call?
Usually yes. Lighthouse gives you both in one tool, without YAML files or separate platforms. Business stakeholders use the visual builder. Engineers write SQL for custom quality checks. One system, one bill.
Does Lighthouse need code to set up data quality checks?
For custom checks, yes — you write SQL. That's a one-time effort per check, not an ongoing YAML project. The visual metric builder handles most business metrics without any code at all.
What warehouses does Lighthouse support?
Snowflake, BigQuery, Postgres, and Microsoft SQL Server. Redshift is on the roadmap. Lighthouse generates dialect-correct SQL per engine — not a generic query pasted across systems.
Business metrics and data quality.
One tool.
Connect your warehouse, set up your first monitor in minutes, and let your whole team stay on top of what matters — no YAML required.
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Comparison based on publicly available information as of May 2026. Soda product details sourced from soda.io. If you spot an inaccuracy, let us know and we'll correct it promptly.