Elastic vs. Zilliz Cloud
Compare Elastic vs. Zilliz Cloud by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.
Elastic vs. Zilliz Cloud on Scalability
Yes.
No. Only scale at the server level.
Yes. At the component level (which provides more fine-grained scalability)
Static sharding
Dynamic segment placement
Elastic scalability
With static sharding, if your data grows beyond the capacity of your server, you will need to add more machines to the cluster and re-shard all of your data. This can be a time-consuming and complex process. Additionally, imbalanced shards can introduce bottlenecks and reduce the efficiency of your system.
Zilliz Cloud
Zilliz Cloud is a managed vector database service powered by Milvus. Its cloud-native architecture dynamically scales to 10B+ vectors, maintaining high performance and cost-efficiency without the need for new clusters or data sharding.
Elastic vs. Zilliz Cloud on Functionality
Performance is the biggest challenge with vector databases as the number of unstructured data elements stored in a vector database grows into hundreds of millions or billions, and horizontal scaling across multiple nodes becomes paramount.
Furthermore, differences in insert rate, query rate, and underlying hardware may result in different application needs, making overall system tunability a mandatory feature for vector databases.
Yes. (combine vector and traditional search)
Yes, Hybrid sparse and dense search, hybrid keyword and vector search, hybrid vector search and scalar filtering, multimodal search
Yes.
1 (HNSW)
Cardinal (The world's first AI-based Autoindex mechanism that selects the best search strategy and index for each dataset, eliminating the need for manual tuning.), closed-source.
Elastic functionality
Elasticsearch uses reverse index and builds vector search capability on top of the exsting search architecture. Elasticsearch is good at text search, but the whole architecture is not purpose-built for vector search.
Zilliz Cloud
Zilliz Cloud is a managed vector database service powered by Milvus. It uses the world's first AI-based Autoindex mechanism that selects the best search strategy and index for each dataset, eliminating the need for manual tuning. It offers intelligent resource management and tiered storage capabilities to minimize expenses while maintaining superior query speeds, ensuring you never compromise performance.
Elastic vs. Zilliz Cloud on Purpose-built
What’s your vector database for?
A vector database is a fully managed solution for storing, indexing, and searching across a massive dataset of unstructured data that leverages the power of embeddings from machine learning models. A vector database should have the following features:
- Scalability and tunability
- Multi-tenancy and data isolation
- A complete suite of APIs
- An intuitive user interface/administrative console
Python, Java, Go, C++, Node.js, Rust, Ruby, .NET (C#), PHP, Perl
Python, Java, JavaScript, Go, C++, and Node.js SDKs Fully supported
Elastic vs. Zilliz Cloud: what’s right for me?
Elasticsearch
Elasticsearch is built on Apache Lucene and was first released in 2010 by Elastic. License: Dual-licensed Server Side Public License (SSPL) or the Elastic License
Zilliz Cloud
Zilliz Cloud is a fully managed vector database powered by the open-source Milvus vector database.
SaaS
