Where Traditional Graphs Struggle… Conode Delivers

Rethinking the Limits of Graph Intelligence—No Code, No Schema, No Prep Needed.

Graphs are powerful. But they’re not perfect - if you use traditional tools.

Spend enough time in data strategy circles and you’ll hear the familiar refrain:

“Don’t use graphs for aggregations.” “Don’t use graphs for search.” “Don’t use graphs for time-based data.” “Use graphs only when relationships matter.”

And they’re not wrong — if you’re using traditional graph databases.

But what if a modern approach could change the rules?

What if the real issue isn’t graphs themselves…

…but the tools we’ve been using to build, explore and actually use them?

Conode redefines what’s possible with graphs—no code, no prep, no barriers.

By combining instant, no-code graph creation with natural language interaction and agent-powered intelligence, Conode makes advanced graph capabilities accessible to any team not just data engineers.

Let’s break down five common graph criticisms—and show how Conode solves each one.

1. “Graphs aren’t good for aggregations.”

Traditional Limitation:

Need to sum sales, average claim durations, or count entities? Use SQL, not Cypher.

✅ Conode’s Advantage:

Conode’s Co-Agents act like analysts—making complex aggregation simple and explainable:

• Natural language group-by and aggregation

• Multi-hop logic across entities (e.g. by risk, region, time)

• Traceable answers with step-by-step context

Example query: “What’s the average severity of mechanical failures by region over the past 3 years?”

→ A non-technical user gets a real, traceable answer - no SQL, no dashboards.

2. “Graphs can’t handle time series data.”

Traditional Limitation:

Tracking sensor readings or minute-by-minute stock ticks? Use a time-series database.

✅ Conode’s Advantage:

Conode handles time-aware graph exploration—making it easy to:

• Detect event sequences or changes

• Compare durations or gaps

• Cluster patterns over time windows

Example query: “Which projects had back-to-back incidents within 60 days of a maintenance window?”

→ Answered using time-aware path traversal across graph-linked events.

3. “Graphs are overkill for key-value lookups.”

Traditional Limitation:

Key-value stores are often seen as the go-to for simple lookups by ID or reference.✅ Conode’s

✅ Conode’s Advantage: 

Conode does more than just find a value—it connects it to meaning.

• Where else has this value appeared?

• What entities or events is it linked to?

• How does it fit into broader patterns or known risks?

Example query: “Find all transactions tied to the same supplier ID that also link to flagged jurisdictions.”→ That’s not just lookup—that’s connected insight with full context.

→ That’s more than lookup—that’s relational context.

4. “Graphs aren’t built for search.”

Traditional Limitation:

Search engines do fuzzy match better. End of story.

✅ Conode’s Advantage:

We agree—and go further.

Conode goes beyond by interpreting what users really want—and delivering contextual, connected answers.

Conode:

• Uses LLM-powered semantic search to retrieve nodes

• Applies structured, context-aware logic through Co-Agents

• Grounds answers in both meaning and structure

Example Query: “Show claims mentioning ‘explosion’ and link them to other similar mechanical failures in wind turbines.”

→ Combines search, structure, and graph pattern logic—no separate tools needed.

5. “Graphs can’t handle disconnected data.”

Traditional Limitation:

If the data isn’t connected, why force it into a graph?

✅ Conode’s Advantage:

Disconnected data is our starting point, not a blocker.

• Upload messy PDFs, emails, or spreadsheets

• Use the Featurizer Agent to extract structured entities

• Automatically construct a dynamic, navigable knowledge graph

Example Query:  “I just uploaded 200 contracts—show me all clauses related to indemnity, and who signed them.”

→ No schema. No modeling. Just answers.

What This All Means

Conode doesn’t try to replace relational databases, vector stores, or search engines.

Instead, it sits above them, turning disconnected, multi-format enterprise data into a live, explainable graph—powered by agents and accessible by anyone.

It’s not about choosing the right database.

It’s about giving your people the power to work with all your data—together, in context, and without friction.

Bottom Line

Traditional Graph Weakness	Conode Turns It Into…
Aggregations	Agent-powered insights
Time awareness	Temporal pattern discovery
Key lookups	Connected context
Search	Structured answers
Disconnected data	Dynamic knowledge graphs

Ready to Rethink Graph Intelligence?

If you’ve written off graphs as too rigid, too technical, or too slow—

Conode might just change your mind.

It’s not just a graph. It’s not just a chatbot. It’s a unified intelligence layer for your enterprise.

Try Conode or reach out for a tailored demo to see how we’re making graphs usable, explainable, and agent-ready for real work.