Head-to-head · updated 13 September 2026

DataShield vs Okera: the product is gone, so what governs your data now?

Let's get the awkward part out of the way. Okera is not a product you can buy. Databricks bought the company in May 2023, and okera.com now redirects to databricks.com. The fine-grained access control you liked, row filters, column masks, tags driving policy, lives on as Unity Catalog ABAC. It is good. It is also only as wide as your Databricks estate.

DataShield is not a lakehouse catalog and we won't pretend to be one. We are the authorization and evidence layer that sits across whatever your agents touch. Datasets are tokenized at ingest; agents query tokenized data over MCP; detokenization is a privileged, audited operation. Every governed call is sealed into a hash chain you can verify yourself. Here is the honest split, including the rows Databricks wins.

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The short version

Pick DataShield when

Your agents reach past the lakehouse. Postgres, Snowflake, S3, a vendor API. One policy plane and one log for all of it, not one per platform.
An examiner will ask you to prove a log wasn't edited. A table the platform wrote, stores, and can rewrite is not proof. Ours is a hash chain with signed checkpoints. Run the verifier.
You need to pull an agent's authority mid-session and have the very next tool call fail.
You want the policy engine, the vault, and the evidence running on your own infrastructure, with keys you hold. See the architecture.

Pick Unity Catalog when

Your data already lives on Databricks. ABAC is native, and there is no second vendor to buy, deploy, or renew.
You want row filters and column masks driven by governed tags, applied to Delta tables at query time. That is Okera's old job, done properly, and we do not do it.
You need automatic lineage from a dashboard back through the tables to the source. Databricks captures that because it runs the compute. We cannot see what we do not sit in front of.
Your governance budget is really a platform budget, and bundling it into DBU spend is easier than a new purchase order.

Bottom line: Unity Catalog governs the data on Databricks. DataShield governs what an agent is allowed to do anywhere, and keeps proof of it. In Databricks shops we expect to run alongside. If your estate is wider than one platform, or the evidence has to hold up on its own, start here.

Feature by feature

Competitor cells describe what Databricks' public site and docs say as of the date above. If we've mischaracterised something, email support@myorg.ai and we'll correct it, credited.

What matters	DataShield	Okera / Unity Catalog	Edge
Product status	Sold and supported as DataShield. Auth is live in production.	Okera is not a standalone product. Databricks bought the company in May 2023 and okera.com redirects to databricks.com. The technology ships as Unity Catalog ABAC.	◆
Fine-grained access control	Scope ceilings and authority tiers on tool tokens, plus quasi-identifier generalization (dates to year, decade or age band; ZIPs to 3 or 4 digits; partial phones, SSNs and emails) with a measured cardinality-reduction score per column. We do not apply row filters to your Delta tables.	ABAC is generally available. Governed tags drive row filter and column mask policies on tables, materialized views, and streaming tables. One policy can cover a whole catalog. DENY policies are still Beta.	◇
Audit evidence	SHA-256 hash chain with Ed25519-signed checkpoints that are themselves chained. Verification names the failure: tampering, insertion, deletion, or truncation. Public verifier.	Audit logs, inference tables, and MLflow traces, stored as lakehouse tables the same platform governs. We found no claim that any of it is hash-chained or signed.	◆
Agent authorization	Every governed tool call passes a scope ceiling, an authority tier, and a revocation re-check before dispatch. Revocation lands mid-session.	Grants and ABAC policies on catalog objects, plus RBAC on models and tools in Agent Bricks. No mid-session authority revocation is described.	◆
Break-glass	Scoped, time-boxed emergency access for agents that auto-revokes and can't be quietly deleted from the log.	Not described in the docs we read.	◆
GDPR erasure	Crypto-shred of per-subject key material plus ISO 27560 consent receipts. The audit chain stays verifiable after erasure.	Delete the rows. Erasure across data copied out of governed tables, and its effect on audit history, is not documented.	◆
Tokenization and data handling	Datasets are tokenized at ingest; agents query tokenized data over MCP; detokenization is a privileged, audited operation. Tokens are deterministic, join-preserving, and vault-reversible.	Masking and redaction applied at query time by policy. We found no vault-reversible token architecture with a governed detokenization path.	◆
Reach beyond the platform	Platform-agnostic. Auth issues MCP tool tokens and the governed surfaces check them on every call, wherever the data sits. Self-hosted, no compute vendor required.	Lakehouse Federation gives governed access to foreign catalogs, but the docs call it read-only with table-level controls. Row and column policy is a Databricks-table story.	◆
MCP and agents	Native MCP endpoints on Auth, Ontology, and Lighthouse. MCP tool tokens with scope ceilings, and per-call metering attributed to the agent.	Managed MCP servers for Genie, SQL, and UC functions ship today, and external MCP clients can connect. Registered as catalog securables, not as per-call authority checks.	◈
Lineage	Typed lineage across the catalog, traversable hop by hop with access gating at each hop, over asset and column records and correlation IDs in the audit chain. It is derived from the pipelines that own the relationships rather than a separate graph store, and it is not column-level lineage across a compute platform.	Automatic lineage across tables, notebooks, dashboards, and models, captured because Databricks runs the query.	◇
Deployment	Self-hosted in your own cloud or data center, or on a dedicated single-tenant server we operate. Your keys.	Databricks control plane on AWS, Azure, or GCP, with a customer VPC data plane. An open-source Unity Catalog server exists but carries a smaller feature set.	◆
Maturity and pricing	Auth, Guardian and Lighthouse are live in production (Guardian and Lighthouse since April 2026). SOC 2 not yet certified, and we say so. Published pricing and an instant quote.	Databricks is a very large private company with a deep enterprise bench. No standalone price for governance: it rides on DBU consumption, quoted by a rep.	◇

◆ DataShield leads◇ Okera / Unity Catalog leads◈ comparable

Databricks claims are drawn from databricks.com and docs.databricks.com, last checked 13 September 2026. We link them below rather than paraphrase from memory.

Three things you get here that you won't get from a lakehouse catalog

A witness that isn't the defendant

The platform that ran the agent should not be the only party attesting to what the agent did. Our chain is held by a separate control plane with its own signing keys. Break it in your browser and watch the verifier name the exact failure. That is the property EU AI Act Article 12 reviewers care about. Try it, no signup.

Authority that can change mid-flight

An analyst leaves on a Friday. Their agent is still grinding through a 40-minute job. With DataShield the next governed tool call is re-checked against current authority and fails closed. A grant revoked in a catalog does not reach into a session already running. How Auth does it.

Governance that outlives the platform choice

Okera buyers learned this the hard way. You picked a layer, the layer got bought, and your policy model went with it. Run the policy plane and the evidence plane yourself, on your own hardware, and a vendor's roadmap stops being your migration plan. How we deploy.

Where Unity Catalog is genuinely stronger

Okera's engineers did not waste three years. Unity Catalog ABAC is generally available, and it is a cleaner product than the standalone one ever was. Tag a column once and the policy follows it across a catalog. Row filters, column masks, materialized views, streaming tables, all handled at query time by the engine that already holds the data. You get lineage for free because Databricks runs the compute. If your data lives on Databricks, turning this on is a config change, and we would tell you to do it before you talk to us.

The push-back is about scope and about proof. Governance stops where the platform stops. Lakehouse Federation reaches foreign catalogs, but the docs are plain that it is read-only with table-level controls, which is a long way from row and column policy on your Postgres. And the audit trail is a set of tables the platform writes and can rewrite. Databricks made our argument better than we could in a blog on 10 September 2026, when they wrote that each catalog must be able to demonstrate compliance independently without administrators reconciling audit trails across systems. We agree. We just think the independent witness should sit above the catalog, not be one of them.

Questions worth asking both of us

These are the questions we'd want answered if we were buying. Ask them on every vendor call, including ours.

What happened to Okera, and is there still an Okera alternative to buy?

Databricks acquired Okera in May 2023. Terms were not disclosed, and okera.com now redirects to databricks.com. The fine-grained access control survives as Unity Catalog ABAC, which is generally available. So the real question is what you wanted Okera for. If it was row and column policy on Databricks tables, use ABAC. If it was a data access governance layer that did not require you to standardise on one compute vendor, that option left the market with the acquisition, and that gap is the one we fill.

Can you cryptographically prove an audit log entry wasn't deleted?

DataShield: yes. Each record commits to the one before it, checkpoints are signed and chained, and verification tells deletion from truncation from tampering. Run it at /verify. Unity Catalog: audit logs, inference tables, and MLflow traces are lakehouse tables. They are rich and queryable. Databricks does not claim they are hash-chained or signed, and we went looking. Ask them to show you the integrity proof.

What happens to a revoked agent mid-session?

DataShield re-checks authority on every governed tool call, so revocation bites on the very next call. Unity Catalog enforces grants and ABAC policies when a query runs, which covers a lot. We found no description of authority tiers for agents or of a session being downgraded in flight. Ask how long a compromised agent keeps working after you pull its access.

How does GDPR erasure interact with the audit trail?

DataShield crypto-shreds the subject's key material and issues an ISO 27560 consent receipt. Actor identities in the chain are HMAC-committed, so the evidence still verifies after the subject is gone. On the Databricks side, deleting rows is straightforward. What the docs do not cover is data already copied out of governed tables, or what erasure does to your audit history. Ask both.

Does DataShield replace Unity Catalog?

No, and we'd be lying if we said otherwise. Unity Catalog is the catalog and the policy engine for your Databricks tables. We do not apply row filters to Delta tables and we do not do platform lineage. Most Databricks customers who talk to us keep Unity Catalog and add an independent layer for agent authorization and tamper-evident evidence. There is more on that in our Unity Catalog write-up.

Does DataShield have SOC 2?

Not yet, and we won't imply otherwise. Auth is live a public threat model and a verifier anyone can run. Guardian and Lighthouse have been in production since April 2026. Design-partner terms include source escrow so a small vendor isn't a single point of failure. Details on the security page.

okera.com returns an HTTP 301 redirect to databricks.com. The standalone product and its site are gone. — okera.com, 13 Sep 2026
"In May 2023, Databricks bought data security group Okera, extending Databricks data governance capabilities." Terms undisclosed. — Wikipedia, Databricks, 13 Sep 2026
Unity Catalog ABAC is generally available: governed tags drive row filter and column mask policies across a catalog or schema. DENY policies are Beta. — docs.databricks.com, 13 Sep 2026
Unity Catalog hero, verbatim: "Unified governance for data, apps and AI agents." — databricks.com, 13 Sep 2026
Lakehouse Federation gives "governed, read-only access to external data through Unity Catalog foreign catalogs," with table-level access controls. — docs.databricks.com, 13 Sep 2026
Databricks: "each catalog must be able to demonstrate compliance independently without requiring administrators to reconcile audit trails across multiple systems." — Databricks blog, 10 Sep 2026

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