vs

Vald vs Vespa

Vald: Kubernetes-native distributed vector search engine built on Yahoo Japan's NGT. Vespa: Big-data serving engine for search, recommendation and RAG with tensors and ML ranking.

key differences

  • Vald is primarily a vector database; Vespa is search engine.
  • Vespa is built for larger datasets (Multi-PB) than Vald (≤ 1 PB).
  • Transactions: Vald offers none ACID; Vespa offers limited.
  • Only Vespa has secondary indexes, full-text search, geospatial, json, ttl / expiry.

choose vald for

  • +Large-scale image or embedding similarity search on Kubernetes
  • +Recommendation candidate retrieval
  • +Internal ANN services

best at · Vector search

choose vespa for

  • +Large-scale hybrid search and RAG retrieval
  • +Recommendation and personalization feeds
  • +Ad serving and ranking
  • +E-commerce search with learned ranking

best at · Search, Vector search, RAG

overview
Primary model
Vector
Search Engine
Also supports
–
Vector, Document
Type
Database engine
Database engine
Status
Active
Active
Developer
LY Corporation (vdaas)
Vespa.ai
First release
2020
2017
Latest version
1.8.0 (Aug 26, 2026)
8.763.13 (Oct 5, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
5.6
23.8
Rank
#382
#127
GitHub stars
1.7K
7.1K
Stack Overflow questions
–
262
scale & guarantees
Comfortable data size
Large (≤ 1 PB)
Massive (Multi-PB)
Horizontal scaling
Native
Native
Multi-region
None
Read replicas
ACID
None
Limited
Consistency
Eventual
Eventual
Schema
Schemaless
Strict
Architecture
Distributed, Client server
Distributed, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
✓
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
–
AWS, Google Cloud, Azure
capabilities
Transactions
—
—
Joins
—
—
Secondary indexes
—
✓
Full-text search
—
✓
Vector search
✓
✓
Geospatial
—
✓
JSON
—
✓
Change data capture
—
—
Triggers
—
—
Stored procedures
—
—
Materialized views
—
—
TTL / expiry
—
✓
Pub/Sub
—
—
Columnar storage
—
—
In-memory
—
—
Durable persistence
✓
✓
Compression
—
✓
Encryption at rest
—
—
Role-based access
—
—
Time travel
—
—
Branching
—
—
Online schema changes
—
✓
Streaming ingest
—
✓
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
Vald gRPC API
YQL
Client languages
Go, Java, Python, Node.js
Java, Python, Go
Best for
Vector search
Search, Vector search, RAG, Real-time analytics

Vald vs Vespa: FAQ

What is the difference between Vald and Vespa?

Vald: Kubernetes-native distributed vector search engine built on Yahoo Japan's NGT. Vespa: Big-data serving engine for search, recommendation and RAG with tensors and ML ranking. Vald is primarily a vector database; Vespa is search engine. Vespa is built for larger datasets (Multi-PB) than Vald (≤ 1 PB). Transactions: Vald offers none ACID; Vespa offers limited.

When should I choose Vald over Vespa?

Choose Vald for large-scale image or embedding similarity search on Kubernetes, recommendation candidate retrieval and internal ANN services. Choose Vespa for large-scale hybrid search and RAG retrieval; recommendation and personalization feeds; and ad serving and ranking.

Is Vald or Vespa more popular?

Vespa ranks #127 on the WhichDB Score (23.8/100) and Vald ranks #382 (5.6/100). Popularity is not fit: check the requirements that matter for your project.

Are Vald and Vespa open source?

Yes. Vald is open source. License: Apache License 2.0. Yes. Vespa is open source. License: Apache License 2.0.