chroma vs. elastic on Scalability
No. Can not scale beyond single node.
No. Only scale at the server level.
No distributed data replacement
Without any distributed data replacement, Chroma is not able to scale beyond a single node
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 vs. elastic 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 with scalar filtering
Yes. (combine vector and traditional search)
Chroma uses HNSW algorithm to support kNN search.
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 vs. elastic 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
chroma vs. elastic: what’s right for me?
Chroma is maintained by a single commercial company offering a non-scalable single node.
License: Apache-2.0 license
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