Hypabase vs Mem0

Different memory models

Mem0 stores flat facts — individual key-value memories like "Alice prefers dark mode" or "User works at Acme Corp." Each fact stands alone.

Hypabase stores structured relationships — edges connecting two or more entities with provenance. "Alice works on the quarterly report with the spreadsheet tool" is one relationship, not three separate facts.

Architectural differences

Mem0

Mem0 stores each fact as an independent memory entry:

mem0.add("Alice is assigned to write the quarterly report", user_id="alice")
mem0.add("Alice uses the spreadsheet tool", user_id="alice")
mem0.add("The quarterly report is due Q3", user_id="alice")

Hypabase

Hypabase stores facts as connected edges with explicit relationships between entities:

with hb.context(source="session_1", confidence=0.9):
    hb.edge(
        ["user_alice", "task_write_report", "doc_quarterly"],
        type="assigned",
    )
    hb.edge(
        ["user_alice", "task_write_report", "tool_spreadsheet"],
        type="uses_tool",
    )

The relationships are explicit. Query them:

# What tools are used for the report task?
report_edges = hb.edges(containing=["task_write_report"], type="uses_tool")

# How are the report and spreadsheet connected?
paths = hb.paths("doc_quarterly", "tool_spreadsheet")
# doc_quarterly → user_alice → tool_spreadsheet

Comparison

	Mem0	Hypabase
Memory model	Flat facts (key-value)	Structured relationships (hyperedges)
Relationships	Not stored	First-class edges connecting N entities
Multi-entity facts	Fragmented into separate memories	Single atomic edge
Provenance	None	Built-in source and confidence
Cross-session queries	Search by user/text	Query by entity, type, source, confidence
Path finding	Not possible	hb.paths(start, end)
Storage	Cloud API	Local SQLite (zero-config)
Retrieval	Text similarity search	Exact structured queries

When to use Mem0 instead

• You only need user preference storage without relationships
• You want managed cloud storage with no local infrastructure
• Your facts stand alone with no connections between them
• You need text-based semantic search over memories

When to use Hypabase instead

• Your agent needs to remember relationships between entities (people, tasks, tools, documents)
• You need to traverse connections between memories
• You need provenance — which session or interaction created each memory
• You need confidence scores to distinguish certain from inferred memories
• You want local-first storage without cloud dependencies

Session-aware memory

Hypabase tracks which session created each memory using provenance context blocks. See the Agent Memory example for a complete multi-session walkthrough.