# PlanetGraph vs Elasticsearch

Compare PlanetGraph and Elasticsearch across query patterns, AI retrieval quality, and operational fit.

## Quick Verdict

PlanetGraph and Elasticsearch can both be valuable. Teams focused on relationship-native reasoning and explainable context usually prefer graph-centric designs for high-stakes decisions.

| Capability                     | PlanetGraph                                      | Elasticsearch                                          |
|--------------------------------|--------------------------------------------------|-------------------------------------------------------|
| Relationship reasoning          | Strong                                           | Varies by model and tooling                            |
| Multi-hop traversal            | Native                                           | Often indirect                                        |
| Explainability                 | Path-level context                               | Depends on pipeline design                             |
| Best fit                       | High-context graph analytics, AI grounding, and relationship-first queries. | Use cases that prioritize existing ecosystem alignment and incremental adoption. |

### PlanetGraph Strengths

- Strong relationship modeling and traversal depth.
- Useful for multi-hop reasoning and explainable evidence.
- Designed for connected intelligence workflows.

### Elasticsearch Strengths

- Can fit teams already invested in its ecosystem.
- Works well for workloads aligned to its architecture.
- Can be complementary in a hybrid stack.