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Vespa vs Weaviate Enterprise Cloud comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 8, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Vespa
Ranking in Vector Databases
19th
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
Open Source Databases (19th)
Weaviate Enterprise Cloud
Ranking in Vector Databases
18th
Average Rating
8.0
Reviews Sentiment
3.9
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Vector Databases category, the mindshare of Vespa is 1.9%, up from 0.8% compared to the previous year. The mindshare of Weaviate Enterprise Cloud is 2.7%, up from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Weaviate Enterprise Cloud2.7%
Vespa1.9%
Other95.4%
Vector Databases
 

Featured Reviews

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reviewer2811174 - PeerSpot reviewer
AI Developer at a tech services company with 11-50 employees
Hybrid search has transformed search relevance and has enabled faster delivery of AI features
I am a strong advocate for Weaviate Enterprise Cloud, but there are areas where improvement would make a real difference. Monitoring and observability could be more robust out-of-the-box. Currently, I rely on external tools such as Grafana to track my cluster performance, and having a native dashboard with deeper query-level insights would be beneficial. I would appreciate SDK parity across languages. Some newer features are available on the Python SDK before they reach Go and TypeScript, which slows down teams working on other languages. The learning curve for advanced configuration, sharding strategies, replication, and tuning schema design can be steep for newer team members, so better-guided workflows or templates would help. Multi-region support is also a pending request for Weaviate to seamlessly join cross-region platforms. Auto-scaling granularity could be smarter. The current scaling responds to overall resource usage, but it would be better if it could scale independently based on query load versus ingestion load, as these spike at different times for me. Backup and disaster recovery flows need to be more flexible. While backups exist, setting up a cross-cloud failover or point-in-time recovery to a specific transaction can still be manual. Native re-ranking integration has been improved, and these are areas where Weaviate needs continued improvement.
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Insurance Company
11%
Computer Software Company
9%
Comms Service Provider
9%
Comms Service Provider
13%
Computer Software Company
11%
Media Company
10%
Educational Organization
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Comparisons

 

Overview

 

Sample Customers

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1. KLM Royal Dutch Airlines 2. Rabobank 3. Philips 4. ING Bank 5. ABN AMRO Bank 6. Booking.com 7. TomTom 8. Randstad 9. Heineken 10. Shell 11. Unilever 12. ASML 13. Ahold Delhaize 14. DSM 15. AkzoNobel 16. VodafoneZiggo 17. NXP Semiconductors 18. Signify 19. Wolters Kluwer 20. Adyen 21. Aegon 22. Arcadis 23. ASR Nederland 24. BAM Group 25. Boskalis 26. Corbion 27. Fugro 28. Galapagos 29. GrandVision 30. IMCD Group 31. Kendrion 32. OCI
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