AutoGen vs Cassandra for real-time apps: Which Should You Use?

AutoGen and Cassandra solve completely different problems. AutoGen is an agent orchestration framework for building LLM-driven workflows; Cassandra is a distributed database built for high-write, low-latency data access at scale. For real-time apps, use Cassandra for the data plane and AutoGen only when you need agentic decision-making on top.

Quick Comparison

When AutoGen Wins

AutoGen wins when the “real-time app” is really a decisioning app with live inputs.

• •

  You need dynamic orchestration between multiple LLM agents

  • •Example: one AssistantAgent classifies an incoming support event, another drafts a response, and a third checks policy compliance before release.
  • •That’s exactly what GroupChat and GroupChatManager are for.
• •

  You need human-in-the-loop approval in the flow

  • •UserProxyAgent is useful when an agent should pause and wait for a person to approve a trade exception, fraud action, or claims override.
  • •Cassandra cannot do that because it stores state; it does not coordinate reasoning.
• •

  You need tool-driven actions based on unstructured input

  • •Example: parse a chat message from a customer, call CRM APIs, summarize account history, then trigger a downstream workflow.
  • •AutoGen’s tool-calling pattern fits this better than trying to force everything into database triggers or application code.
• •

  You’re building adaptive workflows where the path changes per request

  • •If every request can branch differently based on context — escalation paths, policy checks, document review — AutoGen gives you the control loop.
  • •A database will not decide what to do next. It will only persist the result.

When Cassandra Wins

Cassandra wins when you care about hard latency bounds and throughput under load.

• •

  You need fast writes at massive scale

  • •Real-time telemetry, clickstreams, IoT events, order updates — Cassandra is built for this.
  • •Its wide-column model and partitioned architecture are designed for sustained write throughput.
• •

  You need predictable reads by key

  • •If your app fetches session state, account snapshots, presence data, or feed items by known partition key patterns, Cassandra is the right tool.
  • •The SELECT path is fast when your schema matches your access pattern.
• •

  You need horizontal scaling without centralized bottlenecks

  • •Cassandra’s ring-based architecture and replication model are made for distributed deployments across nodes and zones.
  • •That matters in real-time systems where one hot node becomes your outage.
• •

  You need operational durability over AI behavior

  • •For payment event logs, audit trails, notification delivery states, or fraud scoring features that must survive failures cleanly, Cassandra gives you consistency controls like tunable consistency levels.
  • •AutoGen has no answer to durable storage or replayable state.

For real-time apps Specifically

Use Cassandra as the system of record. Use AutoGen only as an optional control layer for workflows that require reasoning over live data. If you try to use AutoGen as your real-time backbone, you’ll get variable latency and unpredictable behavior; if you try to use Cassandra as your agent layer, you’ll get a very fast database that still cannot think.

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.