Kinetica vs Zilliz Cloud
Kinetica
kinetica.com
Zilliz Cloud
zilliz.comSide by side
| Figure | Kinetica | Zilliz Cloud |
|---|---|---|
| Price from | $1.80/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 3 | 4 |
| Spec score · Ai Databases | 8.6 (#6) | 7.3 (#31) |
| Headquarters | Vienna, Virginia, United States | Redwood Shores, California, United States |
| Integrations | Kinetica's vector search page says embedding providers include OpenAI, NVIDIA NIM, and locally hosted models with a compatible inference endpoint. | Documented integrations include Prometheus, Datadog, AWS S3, Azure Blob Storage, Google Cloud Storage, and external model providers. |
| Product | Kinetica describes itself as a distributed, hardware-accelerated database for real-time analytics, combining SQL, vector, graph, time-series, and spatial workloads in one engine. | Zilliz Cloud is a fully managed Milvus service for deploying and scaling vector search applications. |
| Security | Kinetica documents role-based permissions, granular access to tables and schemas, and row and column controls including masking and obfuscation. | Zilliz Cloud documents TLS 1.2 or higher in transit and AES-256 encryption at rest. |
| Support | Kinetica offers Basic, Standard, and Premium support tiers; Premium includes off-hours and weekend coverage, follow-the-sun case management, and monthly incident reporting. | Users can contact Zilliz Support to request access to features in private preview. |
Plans
Kinetica
- Dedicated Cloud$1.80 a month
- Developer EditionFree
- Enterprise EditionPriced on request
Zilliz Cloud
- Free clusterFree
- Business CriticalPriced on request
- DedicatedPriced on request
- ServerlessPriced on request
In their own words
Zilliz Cloud
Zilliz Cloud is a managed Milvus service for deploying and scaling vector search applications. It supports approximate nearest neighbor, filtered, hybrid, and full-text search. Teams can choose Free, Serverless, or Dedicated cluster deployments; Serverless clusters scale automatically to zero. During ingestion, the service can create vector embeddings from raw text using a configured embedding function.
Documented integrations include Prometheus, Datadog, AWS S3, Azure Blob Storage, Google Cloud Storage, and external model providers. Migration sources include Pinecone, Qdrant, Elasticsearch, and PostgreSQL. The service supports sparse vectors, metadata filtering, up to 32768 dimensions, and a range of index types, including FLAT, HNSW, DISKANN, and AUTOINDEX. SDKs are listed for Python, Java, Go, Node.js, and C++. The Free cluster costs nothing and includes 5 GB storage, 2.5M vCUs/month, and up to 5 collections. Dedicated and Serverless pricing is pay as you go; storage charges apply to stored data and backup files even when a cluster is stopped.