What is the best sequence to compare RAG setups?
Start by filtering setup stage, then narrow by license and difficulty to build a shortlist.
RAG Setup Comparison
Last Verified: 2/8/202617 days ago
OrchestrationOpen Sourcemedium
LlamaIndex
Document indexing and RAG workflow composition for application teams.
#RAG#indexing#python
OrchestrationOpen Sourcemedium
LangChain
Composable framework for retrieval, tool use, and multi-step chains.
#framework#agents#retrieval
OrchestrationOpen Sourcemedium
Haystack
Pipeline-oriented stack for enterprise search and RAG systems.
#pipeline#enterprise#retrieval
RetrievalManagedlow
Pinecone
Managed vector database focused on low-ops production retrieval.
#vector-db#managed#scale
RetrievalOpen Sourcemedium
Weaviate
Vector database with hybrid search and flexible schema options.
#vector-db#hybrid-search#self-host
RetrievalOpen Sourcemedium
Qdrant
High-performance vector search engine with payload filtering.
#vector-db#filtering#rust
IngestionOpen Sourcelow
Unstructured
Document parsing and chunk-ready extraction for diverse file types.
#parsing#documents#chunking
IngestionOpen Sourcemedium
Airbyte
Connector-based ingestion to sync source systems into RAG pipelines.
#connectors#sync#etl
EvaluationOpen Sourcemedium
Ragas
RAG-focused evaluation for faithfulness, context precision, and recall.
#evaluation#metrics#quality
OpsManagedlow
LangSmith
Tracing, debugging, and dataset-driven evaluation for LLM apps.
#observability#testing#tracing
OpsOpen Sourcemedium
Arize Phoenix
Open-source observability for embeddings, prompts, and retrieval quality.
#observability#embeddings#monitoring
RAG Setup Comparison FAQ
Should I choose open-source or managed first?
If you have strong MLOps capacity, open-source can fit well. If speed and low-ops are priorities, start with managed options.
What comes after selecting candidate tools?
Run a pilot with 2-3 candidates on your real dataset and validate retrieval quality alongside operating cost.
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