Seemore vs Keebo: two autonomous Snowflake optimizers, built differently

Short answer: Keebo and Seemore Data both cut Snowflake compute cost by changing warehouse settings for you, so this is a closer comparison than most. Keebo says it continuously adjusts warehouse size and auto-suspend within performance guardrails you set, and it also covers Databricks SQL Serverless warehouses, which Keebo lists as a preview.[K1][K3][K5][K7] Seemore plans each warehouse’s size, and in some cases its generation (Gen1 or Gen2), hour by hour, scales up through load spikes, suspends idle warehouses, scales idle clusters back in, and connects each cost to lineage that runs from ingestion and dbt to the dashboard.[S1][S2][S3][S4][S8] Choose Keebo if you want hands-off warehouse tuning across Snowflake and Databricks SQL Serverless. Choose Seemore if you need to explain the bill as well as cut it, and want to approve each sizing schedule before it goes live.

Last reviewed: 14 October 2026. Details about Keebo come from Keebo’s own pages and documentation, listed with their dates in the sources at the end. This market changes fast, so check Keebo’s site before you decide.

At a glance

  Seemore Keebo
Platforms Snowflake; Databricks in Early Access[S10] Snowflake; Databricks SQL Serverless warehouses, listed as a preview[K2][K3]
Changes warehouses automatically Yes: SmartPulse, Burst Protector, Auto-Shutdown and Auto-Scaler[S1][S2][S3][S4] Yes: Warehouse Optimization[K1][K5]
What it changes An hourly size plan and, in some cases, generation (Gen1 or Gen2); extra capacity during load spikes; suspends idle warehouses; scales idle clusters back in; timed manual overrides that revert on their own Size, auto-suspend and cluster values, through algorithms you switch on per warehouse: rightsizing, memory optimization, multi-cluster optimization and proactive suspension[K1][K4][K5]
How changes are governed You approve each SmartPulse schedule before it goes live; optional performance ceiling; Cost or Performance mode per warehouse; every change is in the event log[S1] Guardrails on query latency, queue time and queued queries, on by default since January 2026; Keebo reverts a warehouse to its default settings if one is breached[K5][K7]
Recommendations without changes Recommendations prioritized by effort and savings[S6] Workload Intelligence (Snowflake only) generates recommendations and does not act[K8]
Cost traced to Domain, user, warehouse, job and data product; per Seemore’s FAQ, also pipelines, dbt models, dashboards and teams[S6][S8] Account, warehouse, query and storage; users, roles and query tags in Workload Intelligence[K8]
Lineage Down to column level, with cost, frequency and duration on every node[S6][S8] Not described on the pages we reviewed[K1][K3][K8]
SOC 2 Type II Yes[S9] Yes, since 2023, per Keebo[K10]

Where they are alike

Both tools change Snowflake warehouse settings for you, including size, which not every Snowflake cost tool does. Both say they work from Snowflake metadata rather than your table data: Keebo says it never sees query results, raw data or PII, and Seemore says it does not access, ingest or store raw customer data.[K11][S9] Both say onboarding needs no code changes.[K1][S11] If what you want is to stop paying for oversized and idle warehouses without someone watching them, either one belongs on your shortlist.

Where they differ

What each one decides

Keebo’s Warehouse Optimization works through four algorithms that you choose per warehouse, which Keebo names rightsizing, memory optimization, multi-cluster optimization and proactive suspension.[K5] Keebo’s homepage names warehouse sizing and auto-suspend as levers it tunes, and its FAQ lists size, auto-stop and cluster values as the settings it watches for outside changes.[K1][K4][K5] Keebo’s proactive suspension post, updated on 12 August 2026, describes how it watches each warehouse and suspends it once it has been idle for your target auto-suspend time, within a few seconds of that deadline, instead of relying on Snowflake’s default controller.[K6] Keebo’s release notes say it detects when a warehouse moves between Gen1 and Gen2, and its Workload Intelligence product simulates Gen1 against Gen2 credit use on your own query history.[K7][K9]

Seemore splits the job into separate automations, each with its own controls:

  • SmartPulse learns each warehouse’s usage pattern and turns it into an hourly plan for size and, in some cases, generation (Gen1 or Gen2). It recommends a switch to the other generation only when that generation would cost less or perform better for the workload. It is built for warehouses with a predictable usage pattern; a warehouse too irregular to forecast does not get an automatic schedule.[S1]
  • Burst Protector runs on every SmartPulse-managed warehouse by default. When queries keep queueing beyond what the schedule can absorb, it scales the warehouse up, then back down once the spike passes. In Cost mode it never goes beyond the warehouse’s original configuration; in Performance mode it can step above it, up to a ceiling you set.[S2]
  • Auto-Shutdown suspends a warehouse the moment it stops working, instead of waiting out Snowflake’s idle timeout, and never suspends one with a running or queued query.[S3]
  • Auto-Scaler scales multi-cluster warehouses back in once extra clusters stop contributing, within the minimum and maximum you configured.[S4]
  • Live Tuning lets you make a temporary manual change to size, type or cluster count, from 5 minutes to 24 hours, that reverts on its own.[S5]

How you stay in control

Keebo runs continuously within guardrails you configure: thresholds for query latency, queue time and the number of queued queries. When a guardrail is breached, Keebo reverts that warehouse to its default settings, and guardrails have been on by default since January 2026.[K5][K7] It also detects changes made outside Keebo, and you choose whether it keeps optimizing or pauses on that warehouse.[K5] In September 2026 Keebo opened a private beta of next-generation multi-cluster optimization with custom policies, testing against historical data, hourly grading and a full audit trail of every change.[K7]

For SmartPulse, Seemore asks for approval up front. You see each warehouse’s hourly schedule and approve it before it goes live, and you can pause SmartPulse on a warehouse, revert to a previous schedule or edit the current one. You can set an optional performance ceiling that SmartPulse will never recommend crossing, and choose Cost or Performance mode per warehouse. Every change is recorded in the event log with who made it and when.[S1] Auto-Shutdown and Auto-Scaler act on their own once you switch them on, for the whole account or warehouse by warehouse, and Burst Protector runs with every SmartPulse schedule.[S2][S3][S4]

Both are reasonable designs. Keebo suits teams that want to set guardrails and step away. Seemore suits teams that want to see the sizing plan first.

The context behind each change

This is the biggest difference. Keebo’s optimization is about the warehouse. Its separate Workload Intelligence product, for Snowflake, breaks spend down by account, warehouse, query and storage, and lets you group queries by user, role and query tag, with a by-query-template view.[K8] The pages we reviewed do not describe lineage.[K1][K3][K8]

Seemore connects to dbt, Airflow and BI tools such as Tableau, Looker and Power BI, so it can trace a cost to the models, jobs and dashboards that run on a warehouse.[S7] Its lineage goes down to column level, with cost, frequency and duration attached to every node.[S6] That lets it answer questions beyond “what size should this warehouse be?”, such as which job, dbt model or dashboard sits behind a cost spike.[S8]

When Keebo is the better fit

  • You run Snowflake and Databricks SQL Serverless warehouses and want one optimizer for both.
  • You want continuous tuning within guardrails, and no schedule to review.
  • Your main goal is warehouse efficiency, and you do not need cost traced through pipelines, dbt models and dashboards.

When Seemore is the better fit

  • The Snowflake bill is yours to explain as well as cut, so you need cost by team, data product, job or dashboard.
  • You want to approve warehouse plans before they run, with a performance ceiling.
  • You want warehouse generation (Gen1 or Gen2) considered alongside size, hour by hour.
  • Snowflake is your main platform, and depth there matters more than breadth across platforms.

Is a Snowflake renewal coming up, or did the last bill surprise you? Book a demo to see how Seemore sizes, suspends and scales warehouses for you.

Comparing other options? Read Seemore vs SELECT.

Frequently asked questions

Is Keebo a query routing tool?

Not on its product, documentation or platform pages, although some Keebo blog posts still mention it. Keebo’s documentation lists two products, Warehouse Optimization and Workload Intelligence for Snowflake, and its platform page does not mention routing. Keebo’s former query routing page now redirects to its platform page, and Keebo’s own list of its warehouse algorithms names rightsizing, memory optimization, multi-cluster optimization and proactive suspension. Keebo says it operates outside the query path, yet a Keebo blog post dated 9 October 2026 still refers to a smart query routing feature. If query routing is a requirement, confirm it with Keebo. Checked 14 October 2026.[K3][K5][K11][K12][K13]

Does Keebo suspend idle warehouses itself?

Yes. Keebo’s proactive suspension post, updated on 12 August 2026, describes an algorithm that suspends a warehouse once it has been idle for the target auto-suspend time, after checking that it is still idle.[K6] Seemore’s Auto-Shutdown also suspends a warehouse the moment it stops working, and never suspends one with a running or queued query.[S3]

Does Keebo choose between Gen1 and Gen2?

Keebo says it detects when a warehouse moves between Gen1 and Gen2, and its Workload Intelligence product simulates Gen1 against Gen2 credit use on your own query history. Its Gen1 and Gen2 post describes generation as a setting a system tunes and says Keebo’s engine adjusts warehouse configuration in real time, but we found no explicit statement that Keebo switches a warehouse’s generation for you. Seemore’s SmartPulse compares both generations against each warehouse’s usage pattern and recommends a switch when the other generation would cost less or perform better, as part of the hourly schedule you approve. Checked 14 October 2026.[K7][K9][S1]

Does Keebo support Databricks, and does Seemore?

Keebo covers Databricks SQL Serverless warehouses. Its documentation lists this as Preview, and its September 2026 release notes call it Public Beta.[K2][K3][K7] Seemore for Databricks is in Early Access and covers SQL warehouses (serverless, pro and classic), among other Databricks workloads. See Seemore for Databricks.[S10]

What does Seemore do that Keebo does not?

Seemore traces cost through lineage, down to column level, to the pipeline, dbt model or dashboard behind it, and its SmartPulse plans size and, in some cases, generation as a schedule you approve. The Keebo pages we reviewed describe warehouse optimization and a separate recommendations product, and do not describe lineage. Keebo, for its part, covers Databricks SQL Serverless warehouses today in preview, and runs continuously within guardrails without a schedule to approve. Checked 14 October 2026.[S1][S6][K3][K8]

Sources and dates

Every statement about Keebo comes from Keebo’s own pages and documentation, checked on 14 October 2026 unless a publication date is shown. Every statement about Seemore comes from seemoredata.io as published on the same day.