ClickHouse is fast. We are the platform.
ClickHouse won the column-store performance argument a decade ago. The argument now is whether your data platform is a fast SQL engine — or an autonomous, governed, agent-native operating system. Eisberg is the second one. ClickHouse is the first.
1
policy plane covering query, mask, action, agent
100%
of your data in your bucket, not in our cloud
MCP
agent protocol native, not retrofit
0
stack assembly required to be enterprise-ready
The differences that show up on day 90.
Every line below is something a buyer running ClickHouse for two years has eventually had to confront.
Fast OLAP engine. Not a data platform.
ClickHouse is a brilliant column store. Eisberg is the platform around the column store — governance, lineage, agentic intelligence, business ontology, customer-owned data plane. Buying ClickHouse alone leaves you to build the rest.
ClickHouse owns nothing above the engine.
There's no policy plane, no lineage graph, no agent OS, no tamper-evident audit trail, no business ontology. You assemble those yourself — every customer reinvents the same governance stack on top.
Speed is table stakes. Governance is the moat.
Vectorized execution, columnar layout, modern compression — the industry has converged on these. Speed alone stopped being a differentiator years ago. The question now is what runs on top of speed: governance, lineage, agents, business ontology, a tamper-evident audit trail. Eisberg ships all of that. ClickHouse leaves it to you.
Open format vs proprietary table engine.
ClickHouse stores in its own MergeTree format. Eisberg stores in Apache Iceberg. Iceberg is what Apple, Netflix, and the Fortune 500 are converging on for governed, query-engine-portable data. ClickHouse table engines are a cul-de-sac.
Customer-owned data plane vs ClickHouse Cloud.
ClickHouse Cloud holds your data on ClickHouse infrastructure. Eisberg's data plane is structurally on customer-owned object storage. For regulated industries, that distinction is binary, not gradient.
Agents are an afterthought there. The premise here.
ClickHouse has no agent OS, no per-action metering, no agent governance, no MCP support. Eisberg was designed for the agent era — agent APIs built to a sub-100ms read-path target, risk-graded approval gates, audit trails per agent action.
Snowflake is moving in. That's not a defense — it's a warning.
Snowflake Interactive Analytics is explicitly aimed at the real-time OLAP segment ClickHouse owns — sub-second dashboards, high-concurrency apps, data-powered APIs. Their pricing tells you what they think of the segment: $0.03/GB ingest vs ClickHouse Cloud's $0.04, $23/TB storage vs $25.30. That's a buy-the-market move funded by their warehouse meter. Their answer: a closed warehouse type with a 10-table cap, a 5-second per-query timeout, and a 'real-time streaming' path that's still Private Preview (the GA path is batch refresh with TARGET_LAG in minutes). Both options leave you with single-vendor lock-in — ClickHouse's MergeTree or Snowflake's interactive tier. Eisberg routes embedded and distributed engines over open Iceberg you own, with accelerator lanes composable behind the same router. The open option in a closing market.
The honest head-to-head.
| Capability | Eisberg | Snowflake | Databricks |
|---|---|---|---|
| Knowledge Layer — learns your business from operating | |||
| Tribal knowledge extracted + bound (not just linked) | |||
| Cross-domain stitching (business + software + comms entities) | |||
| Agent certificate enforced at the query chokepoint on customer-owned data | |||
| Compute-layer agent enforcement (not metadata certification) | |||
| Automated business ontology — cross-source, on storage you own | |||
| Customer-owned object storage | |||
| Open format (Iceberg) by default | |||
| Composable multi-engine router (embedded + distributed, over Iceberg you own) | |||
| Sub-100ms agent API targets | |||
| MCP-protocol native | |||
| Per-action agent metering | |||
| Policy-as-code governance at every layer | |||
| Impact-gated autonomous actions (blast radius checked pre-execution) | |||
| Autonomous data classification | |||
| Pipelines that resolve their own failures | |||
| Compounding intelligence across customers (k≥3 anonymity) | |||
| Cost ceiling via outcome pricing |
The questions buyers actually ask.
Show us your ClickHouse setup.
We will model the same workload on Eisberg, show you the projected cost with the math, and demonstrate governance, agents, and lineage running on top.