Alternative
Bigeye Alternative for Self-Serve Data Teams
Bigeye is a strong enterprise observability platform with arguably the best lineage story in the category, including coverage of legacy and on-prem systems. It is also firmly enterprise: there is no pricing page, evaluation runs through a demo, and the public marketplace listing starts at 45,000 dollars a year for 100 monitored tables. Dataobservability covers the same five pillars with column-level lineage, self-serve, from 99 dollars a month.
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Short answer
Bigeye is an enterprise data observability platform (now marketed as an AI trust platform) built around ML autometrics, autothresholds, and deep end-to-end lineage, sold to large regulated enterprises through a demo-led motion. It has no pricing page, and its public AWS Marketplace listing shows Starter at 45,000 dollars for 12 months covering 100 actively monitored tables. Dataobservability delivers the five pillars and column-level lineage self-serve from 99 dollars a month, with no table rationing.
Last updated August 2026
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The same five pillars, self-serve
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Side by side
Dataobservability vs Bigeye
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| Capability | Dataobservability | Bigeye |
|---|---|---|
| 5 pillars of observability | ||
| ML anomaly detection | ||
| End-to-end column-level lineage | ||
| Lineage across legacy and on-prem systems | ||
| Data classification and governance suite | ||
| Self-serve signup, no sales call | ||
| Public list pricing on site | ||
| Entry price | 99 dollars a month | From 45,000 a year (AWS listing) |
Comparison reflects general product positioning and is provided in good faith. Verify current capabilities with each vendor.
What Bigeye actually costs, and the per-table math nobody publishes
Bigeye does not keep a pricing page live, the URL returns a 404, so the only public figures sit on its AWS Marketplace listing. Starter is 45,000 dollars for a 12 month term covering 100 Active Monitored Tables, and Enterprise Starter is 75,000 dollars covering 300. The listing is marked No Refunds, which is worth reading carefully before committing to an annual term. Those two data points are unusually useful because they divide cleanly and expose the volume curve: 45,000 across 100 tables is 37.50 dollars per table per month, and 75,000 across 300 is 20.83. That is a real discount for scale, and it also tells you the entry point is priced for a team that already knows which hundred tables matter. If your warehouse holds a few hundred tables and you want them all watched, price the 300 table tier rather than the entry one, because Active Monitored Tables is the meter and rationing it is what most teams end up doing.
Active Monitored Tables is the meter, and it changes how you use the product
The phrase in the listing is specific. You are billed for the tables monitoring is switched on for, not the tables that exist. On paper that is friendlier than a per monitor meter, because a single table can carry freshness, volume, schema and several field level checks without the bill moving. In practice it creates a different pressure: every table is a yes or no decision with a price attached, so coverage becomes a budget conversation held table by table. Teams handle this by instrumenting the tables they already worry about and leaving the long tail alone, which is precisely the set where unpredicted breakages live. Ask during evaluation how quickly a table can be switched on and off, whether the count is measured at peak or average, and what happens mid term when you cross the tier boundary.
Where Bigeye is genuinely stronger, and it is the lineage
Bigeye has arguably the best lineage story in the category and it is fair to say so. Its coverage extends past the cloud warehouse into legacy and on-prem systems, which matters enormously if your critical data still passes through an Oracle instance, a mainframe extract or an ETL tool nobody has replaced. Most of the modern observability category, including us, connects to Snowflake, BigQuery, Databricks and Redshift and stops there. If your incident post mortems keep terminating at a system outside the warehouse, that gap is the whole decision and no amount of price transparency compensates for it. Bigeye also markets itself as an AI trust platform now, extending the same monitoring posture to model and agent inputs, which is a real direction rather than a rebrand.
Who should not buy Bigeye, stated plainly
Two profiles. The first is a lean team whose data lives entirely in one cloud warehouse. You would be paying for legacy connectivity you will never use, through a demo led evaluation, on an annual term with no refunds, at an entry price around 45,000 dollars. The second is any team that needs to start monitoring this week. There is no self-serve path, no published price and no trial you can start without a conversation, so the shortest realistic path from interest to a monitored table runs through scoping calls and procurement. Dataobservability exists for both cases: the same five pillars and column level lineage, a read-only connection to Snowflake, BigQuery, Databricks or Redshift, published pricing at 99, 299 and 799 dollars per month, and a 14-day trial that takes no card. The honest trade is that we do not reach outside those four warehouses, and Bigeye does.
Honest verdict
Which one should you buy?
Pick Bigeye when
Choose Bigeye if you are a large enterprise with a governance mandate, you need lineage that reaches back into legacy and on-prem systems (a genuine gap in most competitors), you want data classification and stewardship in the same product, and a five-figure annual contract is normal for you.
Pick Dataobservability when
Choose Dataobservability if your data lives in a cloud warehouse, you want the five pillars and column-level lineage running this afternoon, and you do not want to cap how many tables you monitor to stay inside a tier.
Questions buyers ask
Bigeye alternative FAQ
How much does Bigeye cost?
Bigeye does not publish pricing on its site (bigeye.com/pricing returns a 404) and sells through a demo. Its public AWS Marketplace listing shows Starter at 45,000 dollars for a 12-month contract covering 100 actively monitored tables, and Enterprise Starter at 75,000 dollars covering 300 tables. Both include two Core Lineage Plus connectors and the browser extension. Bigeye defines an actively monitored table as one you have data quality and pipeline monitoring applied to, so tables that are connected but not monitored do not count against the cap. The listing states no refunds. The table caps matter as much as the price if your warehouse is wide. Checked directly on the AWS Marketplace listing in August 2026.
What is the best Bigeye alternative?
For cloud-warehouse teams that want the same five pillars and column-level lineage without a five-figure contract and a table cap, Dataobservability is the closest self-serve fit at 99 dollars a month. If your requirement is lineage across legacy and on-prem systems plus formal governance and data classification, Bigeye is genuinely strong there and worth the enterprise motion.
Does Bigeye have a free trial?
Not of the core observability product. Bigeye offers a narrow 30-day trial of its Agent Trust Hub, limited to specific ecosystems, and routes everything else through a demo request. Dataobservability offers a 14-day free trial of the full product with no credit card, and you connect a read-only warehouse role yourself.
Is Bigeye still a data observability tool?
Yes, though it now markets itself as an enterprise AI trust platform built on its lineage and observability technology. Monte Carlo made a similar move toward agent and AI trust positioning. The underlying monitoring (autometrics, autothresholds, lineage) is still there, but the product is being sold into a broader governance and AI story.
Other comparisons
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