Machine Learning · head to head
LangChain vs Traceloop

LangChain
Machine Learning
Build applications with LLMs through composability
- From
- Free
- Rated
- -

Traceloop
Logging
LLM reliability platform with open-source observability and evaluation
- From
- Free
- Rated
- -
The short version
- Each has a real cost: LangChain the free Developer plan of LangSmith is limited to 1 seat; Traceloop free tier limited to 50k spans per month and 24-hour retention, restricting production use
- They diverge on capability: LangChain covers Chains and agents, Traceloop covers Open-source SDK (OpenLLMetry).
Where they differ
Only the attributes on which LangChain and Traceloop actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in LangChain
- Chains and agents
- Retrieval-augmented generation
- Memory management
- Tool integration
- Prompt templates
- OpenAI
- Anthropic
- Hugging Face
Only in Traceloop
- Open-source SDK (OpenLLMetry)
- Multi-provider support
- Observability platform integration
- Framework support
- Monitoring dashboard
- Evaluation system
- Deployment flexibility
What people use each for
The jobs each tool is most often brought in to do.
LangChain
- Building LLM applications and agents in Python or JavaScriptnot Traceloop
- Tracing and debugging LLM chains and agent runsnot Traceloop
- Evaluating prompt and model changes against datasetsnot Traceloop
Traceloop
- Monitoring LLM application performance in productionnot LangChain
- Instrumenting LLM apps with minimal code overheadnot LangChain
- Continuous evaluation and quality scoring of LLM outputsnot LangChain
- Debugging LLM application issues with full trace visibilitynot LangChain
- Integrating observability data into existing monitoring stacksnot LangChain
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
LangChain
- The free Developer plan of LangSmith is limited to 1 seat
- Base traces are retained for 14 days only; 400 day retention costs extra
- Included traces are capped at 5,000 per month on Developer and 10,000 per month on Plus, with everything beyond billed pay as you go
- Self hosted and hybrid deployment of LangSmith is Enterprise only
- Custom SSO, RBAC and ABAC are Enterprise only
- A support SLA is Enterprise only
- Enterprise pricing is by quote with no published rate
Traceloop
- Free tier limited to 50k spans per month and 24-hour retention, restricting production use
- Company acquisition by ServiceNow creates uncertainty about future roadmap
- Requires integration with separate observability platforms for visualization
- Less feature-rich than dedicated LLM evaluation platforms
Pricing, plan by plan
LangChain
Free- Open SourceFree
- Full framework
- Community support
- LangSmith$39/month
- Debugging
- Monitoring
- Testing
Traceloop
Free- FreeFree
- 50,000 spans per month
- Up to 5 seats
- 24-hour data retention
- Enterprise$undefined/custom
- Unlimited spans per month
- Unlimited seats
- Custom data retention
Which should you pick?
Choose LangChain if
- You need chains and agents.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want retrieval-augmented generation.
Choose Traceloop if
- You need open-source sdk (openllmetry).
- You want to start without paying.
- You work on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
- You also want multi-provider support.
Questions people ask
- Is LangChain or Traceloop better?
- Neither clearly leads. LangChain starts at Free and Traceloop at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, LangChain or Traceloop?
- LangChain starts at Free and Traceloop at Free.
- Does LangChain or Traceloop run on more platforms?
- LangChain runs on Linux, Mac, Windows. Traceloop runs on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
- Can I use LangChain for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is LangChain best used for?
- LangChain is most often used for building llm applications and agents in python or javascript, tracing and debugging llm chains and agent runs, evaluating prompt and model changes against datasets. Of those, building llm applications and agents in python or javascript and tracing and debugging llm chains and agent runs are not what Traceloop is typically brought in for.
- What can LangChain do that Traceloop cannot?
- LangChain covers Chains and agents, Retrieval-augmented generation, Memory management, Tool integration. Traceloop covers Open-source SDK (OpenLLMetry), Multi-provider support, Observability platform integration, Framework support.
Answered from the vendors’ own pages
LangChain: Does LangChain charge for its services?
LangChain's main website does not display pricing. However, LangSmith (a related platform) offers both free and paid plans. Visit the dedicated pricing page or contact LangChain for details.
SourceTraceloop: Is OpenLLMetry open-source?
Yes, OpenLLMetry is Traceloop's open-source SDK built on OpenTelemetry standards. It allows teams to instrument LLM applications with just 2 lines of code and send data to 25+ observability platforms.
SourceLangChain: How can I learn about LangChain pricing?
Click on the Pricing link in navigation or use the Try LangSmith or Get a demo options to explore pricing for LangChain's commercial offerings.
SourceTraceloop: What is the impact of ServiceNow acquisition?
Traceloop is joining ServiceNow, representing a strategic acquisition that will broaden enterprise adoption and integration capabilities. Current operations continue with free and enterprise options available.
SourceTraceloop: How many LLM providers and frameworks does Traceloop support?
Traceloop supports 20+ LLM providers including OpenAI and Anthropic, and integrates with frameworks like LangChain and LlamaIndex. It can send data to 25+ observability platforms.
SourceRelated pages
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- Traceloop vs Google Vertex AI
- Traceloop vs Azure Machine Learning
- Traceloop vs DataRobot
- Traceloop vs MLflow
- Traceloop vs Snowflake
- Traceloop vs TensorFlow
- Traceloop vs Comet ML
- Traceloop vs Jupyter
- Traceloop vs Pinecone
- Traceloop vs Python
- Traceloop vs PyTorch
- Traceloop vs scikit-learn
- Traceloop vs Apache Spark MLlib
- Traceloop vs Weaviate
- Traceloop vs Weights & Biases
- Traceloop vs Alteryx
- Traceloop vs Anaconda
- Traceloop vs Elastic Stack
- Traceloop vs New Relic
- Traceloop vs Datadog Logs
- Traceloop vs Coralogix
- Traceloop vs Grafana Loki
- Traceloop vs incident.io
- Traceloop vs Cronitor
- Traceloop vs FireHydrant
- Traceloop vs Healthchecks
- Traceloop vs Openstatus
- Traceloop vs Rootly
- Traceloop vs Checkly
- Traceloop vs CloudWatch
- Traceloop vs Dynatrace
- Traceloop vs InfluxDB
- Traceloop vs Airbrake
- Traceloop vs AppDynamics
- Traceloop vs Axiom
