Vespa Cloud Subscription

What do you like best about the product?

We purchased the Enclave product which was really well-suited for us because it let us run the hosts in our own Google cloud account (at our pricing with Google), and thus didn't require us to transfer any data out which was well-aligned with our security stance. It provided light-touch deployment and observability services that we lacked and helped us bootstrap quickly and with minimal investment.

The Vespa search backend itself provided a good match to our requirements of near-real time hybrid search, combining nearest neighbor embedding search with attribute filters, in a distributed and highly scalable way. Our target installation comprised >12TB of memory across 24 hosts and held O(1B) vector embeddings.

What do you dislike about the product?

Vespa, in a scalable deployment, presents a fairly complex architecture with a lot of tuning knobs and bells and whistles. It took several months to get familiar with them. The Vespa consultant was very instrumental in this. Feeding Vespa from BigQuery was harder than expected.
Native extensions can only be written in Java which, without a native Java toolchain at our company, proved too challenging to pursue. The documentation is vast but could be better organized and have more contextual examples in places.

What problems is the product solving and how is that benefiting you?

We used the Vespa search backend for hybrid search, consisting of nearest neighbor search of indexed embeddings vectors and attribute filters. This powered a natural-language image search product for our internal users.

What do you like best about the product?

I like the open-source and free 300 dollar cloud credits for hosting the live applications.

What do you dislike about the product?

I feel there should be more documentation work is in pending and needed as I am still exploring the AI and vector database part.

Anyway I am happy to contribute for open source as a contributor.

What problems is the product solving and how is that benefiting you?

I worked for my e-commerce client to highlight the product which are giving more sales by ranking and recommendations for efficiency in stock.

What do you like best about the product?

I can create recommendation applications and deploy real-time machine learning inference using this stack. Such a level of functionality is what we need for our large scale search applications.

What do you dislike about the product?

Vespa initialization and subsequent functioning, in fact, require a significant level of system configuration. It may be a little obscure sometimes and for troubleshooting issues one has to really appreciate the underlying environment.

What problems is the product solving and how is that benefiting you?

Vespa solves the problem of managing and processing large amounts of data and its integration with Artificial Intelligence for Web applications. It enables me to build outstanding search capabilities and I use real-time data processing.

What do you like best about the product?

In the case of my recommendation engine, Vespa replaces other systems, thus minimizing issues related to architecture and deployment. Enabling me enhance the search by including the AI models in the process for more unique outcomes.

What do you dislike about the product?

Using ready-made machine learning models in Vespa may present some difficulty to developers. This particular aspect seems to be quite under-documented and the options provided look slightly unnatural.

What problems is the product solving and how is that benefiting you?

Vespa has been useful in composing my huge recommender system. The features of the unified search platform and real time AI inference help me provide customers with powerful relevant information.

What do you like best about the product?

The most helpful thing is the open source big data engine, heps to process and serve large scale data in real time with very low latency time.Its content recommendations are very useful for the modern day real-time analysis. Also, it is more flexible and scalable with advanced query techniques which makes it more easy to use.

What do you dislike about the product?

Integrating vespa with existing systems and workflows can be challenging, particulary if systems were based on different technologies. Documentation and customer support for an open source is not at the top notch when compared to the real time products. since it is highly specialised it may overkill for simpler applications w or less demanding requirements.

What problems is the product solving and how is that benefiting you?

Vespa helps in solving real time updates by using as a search engine which gives lot of recommendations based on our search results. it has the scalability and flexibility to process large volume of data in real time analyses and in turn produces intelligent responses based on the latest data.