PointFive Alternative: LakeSentry for Databricks Cost
A Databricks-only alternative to PointFive. Compare scope, remediation model, and pricing — based on each product's public materials.
LakeSentry is a Databricks cost intelligence platform with public per-user pricing and guided optimization plans — it stays read-only, and your team applies every change in Databricks. If you are evaluating PointFive, here is how LakeSentry compares on scope, remediation model, and pricing.
This page is based on each company’s current public materials as of May 2026.
What each product is
PointFive
PointFive positions itself as a cloud and AI efficiency platform — “extend your coverage to every resource and layer to create a single source of truth for Cloud, Data, PaaS & AI Services cost efficiency.” Its DeepWaste detection spans cloud infrastructure, data platforms, and AI services. On Databricks it lists 60+ detections: DBU, compute, storage, and serverless visibility; per-job serverless attribution; cluster right-sizing; multi-node waste; storage and Time Travel optimization; and ML serving rightsizing. It deploys agentless and read-only through a single notebook run. Remediation is agentic but human-reviewed: it generates infrastructure-as-code fixes (Terraform, CloudFormation) that engineers review and approve, with routing into Jira, Slack, or ServiceNow.
LakeSentry
LakeSentry is purpose-built for Databricks. It connects read-only through a service principal, queries system tables, and normalizes the cost ledger across workspaces: spend by job, SQL warehouse, compute type, and team, plus anomaly detection with statistical evidence. Every recommendation ships as a guided plan your team applies in Databricks; LakeSentry itself stays read-only.
Different scope
PointFive’s coverage spans cloud infrastructure, several data platforms, PaaS, and AI services, with Databricks as one layer within that wider picture. LakeSentry covers Databricks only.
LakeSentry’s cost ledger, its use of system tables as the source of truth, and Unity Catalog as the access boundary are all built around the Databricks model. PointFive’s surface extends from cloud infrastructure through data platforms to AI inference.
If Databricks is the layer you are optimizing, LakeSentry’s scope is specific to it. If you want to find waste across the whole cloud estate from EC2 to AI inference in one tool, PointFive covers that wider surface.
Similar deployment, different remediation
Both products connect read-only. Each deploys agentless and authenticates through a service principal with minimal permissions. PointFive keeps write access optional; LakeSentry never asks for it.
The remediation paths differ:
- PointFive generates fixes as infrastructure-as-code (Terraform, CloudFormation) that your engineers review and approve before deploying, with routing into Jira, Slack, or ServiceNow.
- LakeSentry delivers each finding as a guided plan in-product: the evidence, the exact change proposed, and the current value it would replace, ranked by dollar impact. Your team applies it in Databricks; approvals and dismissals are admin-only and land in an audit log.
Both keep a human in the loop. The difference is what arrives in your hands — generated infrastructure-as-code to review and deploy, or a reviewed plan with the evidence attached that your own team applies.
Pricing
LakeSentry’s pricing is published on lakesentry.io:
- Free: $0/mo — 1 user, 3 months history, unlimited connected workspaces
- Standard: $499/mo (billed annually) — up to 5 users, 12 months history
- Pro: $849/mo (billed annually) — unlimited users, unlimited history
There are no per-DBU and no per-workspace fees.
PointFive’s pricing is annual and scales with the cloud spend it covers; its Databricks page cites a ratio of “less than $35/month per $1M of Databricks spend,” with larger tiers quoted by contract. The structural difference: PointFive’s cost tracks the spend it covers, while LakeSentry’s tracks your user count and stays flat as your Databricks bill grows or shrinks.
Which is lower depends on your numbers. Spend-tiered pricing rises with the bill it covers; flat per-user pricing stays the same as spend changes.
At a glance
| PointFive | LakeSentry | |
|---|---|---|
| Category | Cloud + data + AI efficiency platform | Databricks cost intelligence |
| Scope | Cloud infra, multiple data platforms, AI services | Databricks-only |
| Deployment | Agentless, read-only, notebook + service principal | Read-only, service principal |
| Remediation model | AI-generated IaC fixes, engineer-approved | Guided plans with evidence, applied by your team |
| Pricing | Annual, scales with spend covered | Flat per-user: $0 / $499 / $849/mo (billed annually) |
| Free tier / trial | No free tier; demo (also on AWS Marketplace) | Free: 1 user, 3 months history, unlimited workspaces |
Choose PointFive if
- You want one efficiency layer across cloud infrastructure, data platforms, and AI services
- Reviewing and deploying AI-generated infrastructure-as-code fixes fits how your engineers work
- Annual pricing that scales with the spend it covers suits your budgeting
- DeepWaste detection beyond Databricks is part of what you are buying
Choose LakeSentry if
- Databricks is your focus and you want cost attribution and anomaly depth there
- You want the evidence and the proposed change in one place rather than IaC-and-ticketing remediation
- Flat per-user pricing that stays the same as spend changes fits your procurement
- You want a single cost ledger across all your Databricks workspaces
Common questions
Do the two overlap on Databricks?
Yes, on detection. Both surface Databricks waste. PointFive does this as part of a cloud efficiency platform; LakeSentry does it with Databricks-specific attribution.
How does remediation differ?
Both connect agentless and read-only. PointFive delivers fixes as infrastructure-as-code that engineers review and approve; LakeSentry delivers guided plans in-product — the evidence, the exact change, and its expected effect — which your team applies in Databricks.
What if my waste is not only in Databricks?
PointFive’s coverage spans the whole cloud estate. LakeSentry’s coverage is Databricks, where it goes into per-job and per-team attribution.
For the full category view, see the Databricks cost tools comparison, or read how LakeSentry approaches Databricks cost optimization.
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