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ObsessionDB
Managed ClickHouse hosting with an NVMe cache mesh that keeps p99 latency flat as data grows
0Visit ObsessionDB
https://obsessiondb.com
About ObsessionDB
ObsessionDB is managed ClickHouse hosting built around a single complaint: on most managed ClickHouse services the bill scales faster than the query volume, so teams end up paying substantially more each year just to hold latency where it already was. The architecture answer is a cache mesh — a cluster of NVMe-backed nodes that keep hot data resident in the query path, with S3 used as a write-only durability layer that never sits between a client and its results. The practical effect the vendor publishes is that p99 latency stays flat as a dataset grows from one terabyte to a petabyte while cost per query falls, which inverts the usual pattern where both degrade together. Clients connect over ordinary SQL through the standard ClickHouse drivers, so it is a hosting swap rather than a migration to a new query language. The pricing page is a live calculator rather than a plan ladder: you set compressed storage, memory per node and node count, pick a workload preset for real-time, observability or BI shapes, and it prices the cluster against a one-to-one comparison with other managed ClickHouse offerings. Ingress and egress are not metered. There is a free developer instance for evaluation, and the team offers a performance audit before you commit, which suits the case where you already run ClickHouse somewhere and want the comparison on your own workload rather than on a benchmark.
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Key Features
ObsessionDB Pros & Cons
✅ Pros
- +Cost-per-query improving with scale is the opposite of the usual managed-ClickHouse curve
- +Standard SQL and drivers make it a hosting swap rather than a rewrite
- +Free egress removes the usual hidden line item on analytical workloads
⚠️ Cons
- −Entry pricing lands in the thousands per month — not a hobby-project database
- −Benchmarks are vendor-published on their own customer workloads
- −ClickHouse-only, so it does not help if your analytics live elsewhere
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