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turbopuffer vs Agno

turbopufferAgno

Bottom line: turbopuffer for multi-tenant SaaS with per-customer indexes; Agno for python teams building agents.

turbopufferturbopuffer

Serverless vector and full-text search built on object storage

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AgnoAgno

High-performance Python framework for building multi-agent systems and AgentOS

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Votes00
PricingPaidFreemium
CategoryVector DatabasesAgent Frameworks
Tags
vector-databaseserverlessobject-storagefull-text-searchrag
multi-agentpythonagentopsragopen-source
Best for
  • Multi-tenant SaaS with per-customer indexes
  • Cost-conscious large-scale RAG
  • Teams with mostly-cold data
  • Python teams building agents
  • Teams wanting predictable flat pricing
  • Multi-agent system builders
Pros
  • Extremely cheap storage on object storage (~$0.02/GB)
  • Pure usage-based pricing with strong volume discounts
  • Great fit for many cold namespaces (multi-tenant)
  • Vector and full-text search in one engine
  • Query rate reduced to $1/PB in 2026
  • Performance-focused, Python-first design
  • Full local control plane free of charge
  • Flat pricing with no token or egress fees
  • Built-in knowledge, memory, and evals
  • Model-agnostic across major providers
Cons
  • No free plan; monthly minimums apply
  • Managed-only — no self-hosting
  • Cold namespaces have higher first-query latency
  • Pricing model requires understanding usage patterns
  • Younger product than established vector DBs
  • Python-only framework
  • Pro plan starts relatively high at $150/month
  • Additional connections and seats add up
  • Rebrand from Phidata may cause some confusion
  • Ecosystem younger than the largest frameworks

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