Elastic vs. Chroma
Compare Elastic vs. Chroma by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.
Elastic vs. Chroma on Scalability
No. Only scale at the server level.
No. Can not scale beyond single node.
Static sharding
No distributed data replacement
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.
Chroma scalability
Without any distributed data replacement, Chroma is not able to scale beyond a single node
Elastic vs. Chroma 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 with scalar filtering
1 (HNSW)
1 (HNSW)
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.
Chroma functionality
Chroma uses HNSW algorithm to support kNN search.
Elastic vs. Chroma 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, JavaScript
Elastic vs. Chroma: 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
Chroma
Chroma is maintained by a single commercial company offering a non-scalable single node. License: Apache-2.0 license
