ObsessionDB vs Supabase: Which is Better in 2026?
A comprehensive comparison of ObsessionDB and Supabase covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose ObsessionDB if:
- →You need nvme cache mesh keeps hot data in the query path with 100% cache hit targets or s3 persistence is write-only and never sits in the query path
Choose Supabase if:
- →You want more affordable paid plans (from $25/mo)
- →You need postgresql database or pgvector embeddings
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ObsessionDB vs Supabase: At a Glance
Pricing Comparison: ObsessionDB vs Supabase
Understanding the pricing differences between ObsessionDB and Supabase is crucial for making the right choice. Here's how their plans compare side by side.
ObsessionDB Pricing
💡 Pricing takeaway: Both ObsessionDB and Supabase offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from ObsessionDB and Supabase stacks up.
What Makes Each Tool Unique
🔵 Unique to ObsessionDB
Features available in ObsessionDB but not in Supabase:
- ✓NVMe cache mesh keeps hot data in the query path with 100% cache hit targets
- ✓S3 persistence is write-only and never sits in the query path
- ✓Live sizing calculator that prices against other managed ClickHouse one-to-one
- ✓Free ingress and egress
- ✓Workload presets for real-time, observability and BI shapes
- ✓Free developer instance and a pre-commitment performance audit
🟣 Unique to Supabase
Features available in Supabase but not in ObsessionDB:
- ✓PostgreSQL database
- ✓pgvector embeddings
- ✓Auth & row-level security
- ✓Edge Functions
- ✓Realtime subscriptions
- ✓File storage
Use Case Recommendations
Best for: 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.
Ideal use cases:
- •Teams or individuals who need nvme cache mesh keeps hot data in the query path with 100% cache hit targets
- •Teams or individuals who need s3 persistence is write-only and never sits in the query path
- •Teams or individuals who need live sizing calculator that prices against other managed clickhouse one-to-one
- •Teams or individuals who need free ingress and egress
- •Anyone focused on clickhouse workflows
- •Anyone focused on olap workflows
Best for: Supabase
Open-source Firebase alternative with built-in pgvector for AI applications. Supabase provides a PostgreSQL database, authentication, storage, and vector embeddings for building AI-powered apps.
Ideal use cases:
- •Teams or individuals who need postgresql database
- •Teams or individuals who need pgvector embeddings
- •Teams or individuals who need auth & row-level security
- •Teams or individuals who need edge functions
- •Anyone focused on database workflows
- •Anyone focused on backend workflows
📊 Other Data & Analytics Tools to Consider
ObsessionDB and Supabase aren't the only options. Here are other popular tools in the same space:
Databricks AI
Enterprise AI and data lakehouse platform
Akkio
No-code predictive AI for business analysts
Hex
Data workspace with AI analysis and apps
MindsDB
AI layer for databases with SQL ML
Obviously AI
No-code ML platform for predictions
Julius AI
Chat with your data for instant analysis
Is one of these your tool?
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Frequently Asked Questions
Is ObsessionDB better than Supabase?
It depends on your needs. ObsessionDB offers 6 key features including NVMe cache mesh keeps hot data in the query path with 100% cache hit targets and S3 persistence is write-only and never sits in the query path, while Supabase provides 6 features including PostgreSQL database and pgvector embeddings. ObsessionDB uses a freemium model with a free tier, while Supabase is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is ObsessionDB cheaper than Supabase?
Supabase is cheaper, starting at $25/month compared to ObsessionDB's $3,840/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use ObsessionDB and Supabase together?
Yes, many users combine ObsessionDB and Supabase in their workflow. ObsessionDB excels at nvme cache mesh keeps hot data in the query path with 100% cache hit targets, while Supabase shines with postgresql database. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between ObsessionDB and Supabase?
While both are data & analytics tools, ObsessionDB emphasizes nvme cache mesh keeps hot data in the query path with 100% cache hit targets, whereas Supabase is known for postgresql database. The best choice depends on your specific workflow and feature priorities.
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