MyScale | Run Vector Search with SQL
Depends
Confidence: Medium
Buy if you're a SQL-heavy team running RAG or semantic search at real scale and have outgrown Postgres.
New check
Comparison
MyScale | Run Vector Search with SQL and Zilliz Vector Lakebase for Enterprise AI, Powered by Milvus both land on Depends.
Buy if you're a SQL-heavy team running RAG or semantic search at real scale and have outgrown Postgres.
Buy if you run production AI search at serious scale or already standardize on Milvus.
| Compare | MyScale | Run Vector Search with SQL | Zilliz Vector Lakebase for Enterprise AI, Powered by Milvus |
|---|---|---|
| Verdict | Depends | Depends |
| Best for | SQL-first AI teams | Enterprise RAG at billion-vector scale |
| Who it's not for | Anyone not yet outgrowing Postgres + pgvector | Small apps with a few thousand vectors |
| Privacy | No known public vulnerabilities found in the sources reviewed.⁶ | No known public vulnerabilities found in the sources reviewed. |
| Support quality | No support evidence in reviewed sources | No support evidence found |
| Public sentiment | Independent user feedback is thin; the strongest signal is a 4.6/5 G2 rating, while Reddit and Hacker News posts about MyScale are largely vendor-authored.¹ | Marketplace users praise performance, scalability, and low latency, while independent feedback on the new Lakebase tier is still scarce.15 |
| Biggest gotcha | Guess: managed pod pricing can scale fast with vector volume . confirm overage terms before committing. | Usage-based billing across storage, compute, and search can spike costs |