At a glance
| Supported data platforms | Snowflake, Databricks, BigQuery, Redshift, Athena, Synapse, SQL Server, Oracle, PostgreSQL, MySQL, Db2, SAP HANA, Teradata, Trino |
| Anomaly detection | Metrics with automatic thresholds from history |
| Freshness and volume monitoring | Yes, FRESHNESS and VOLUME table metrics |
| Schema checks | Not documented in the pages checked |
| Validation rules | Custom thresholds and configuration-as-code (bigConfig) |
| Lineage and root cause | Column-level lineage (Lineage Plus), lineage-enabled monitoring |
| Alerting | Slack, Teams, PagerDuty, Jira, ServiceNow, webhooks |
| Deployment | SaaS with agentless or self-hosted agent connections |
| Licensing | Commercial subscription, quote only |
Bigeye suits enterprises that mix cloud warehouses with older platforms such as Teradata, Netezza, Db2 or Oracle and want lineage-aware monitoring across both. It is quote-only with no trial, and its newer AI governance modules widen the scope, so be clear which modules you are being priced for.
Overview
Bigeye monitors tables in data warehouses and databases by collecting table and column metrics (bigConfig lists FRESHNESS and VOLUME among the table metrics), and it sets thresholds automatically from history so you do not have to hard-code limits; custom thresholds are also possible. Its Lineage Plus feature builds column-level lineage across modern and legacy sources, and lineage-enabled monitoring can extend coverage to the upstream dependencies of an important asset.
Many sources connect agentlessly, while a Data Source Agent, deployed with Docker or Kubernetes and managed from the Bigeye UI, connects warehouses that should not be reached directly from the vendor's cloud. Configuration can be kept in files with bigConfig, and Deltas compares similar datasets to check replications, migrations or model code changes. The current product adds metadata management, sensitive data classification and AI governance modules.
Key features
- Automatic thresholds learned from metric history, with optional custom thresholds
- Lineage Plus: automated column-level lineage across modern and legacy data sources
- bigConfig for managing monitoring as configuration-as-code
- Deltas for comparing datasets during replication, migration or model changes
- Agentless connections plus self-hosted Data Source Agents on Docker or Kubernetes
- Sensitive data scanning and classification, and AI policy enforcement modules
- Alerts and tickets through Slack, Microsoft Teams, PagerDuty, Jira, ServiceNow and webhooks
Integrations and ecosystem
Pros and cons
Pros
- Documented connectors for legacy platforms (Teradata, Netezza, Db2, Greenplum) as well as cloud warehouses
- Column-level lineage across those sources
- Monitoring as code with bigConfig
- Self-hosted agent option for sources that must not be exposed
Cons
- No public pricing, free tier or trial
- Broad AI governance positioning can make scope and price harder to compare with monitoring-only tools
- Self-hosted agents need Docker or Kubernetes operations on your side
Pricing
Bigeye publishes no prices, plans or pricing units. Its pricing page only offers a demo booking and a short interactive product tour; no free tier or self-service trial is advertised. Expect a quote based on your estate and the modules you need.
Pricing checked on the vendor's official page on 7 November 2026. Prices change; confirm before buying.
Who it is best for
Large organisations with a mix of cloud warehouses and legacy databases that want lineage-aware data monitoring and are prepared to buy an enterprise subscription.
Typical use cases
- Monitor freshness and volume on Teradata or Oracle tables that feed a Snowflake migration
- Verify a replication or migration with Deltas dataset comparisons
- Map column-level lineage from source systems to Tableau or Power BI reports
- Keep monitor definitions in Git with bigConfig
Who should look elsewhere
- Teams that want a free or open source starting point: see GX Core or Elementary.
Verdict
Bigeye is a credible enterprise data observability choice, particularly where legacy databases sit beside cloud warehouses and column-level lineage matters. With no public pricing and an expanding AI governance scope, buyers should scope the monitoring modules carefully and compare quotes.
Frequently asked questions
How much does Bigeye cost?
Bigeye does not publish prices. Its pricing page offers a demo and a product tour, and pricing is by quote.
Does Bigeye need an agent?
Not always. Bigeye documents agentless connections for many sources and a self-hosted Data Source Agent, run on Docker or Kubernetes, for warehouses you do not want to expose to its cloud.
What is bigConfig?
bigConfig is Bigeye's configuration-as-code format for defining data observability monitoring in files, so monitor definitions can be reviewed and versioned like code.
Sources
Checked November 2026.
Listed in: Data Quality & Observability.
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