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Based on our record, Vespa.ai should be more popular than Snowflake. It has been mentiond 19 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Snowflake, a data warehousing company founded by ex-Oracle and ex-VectorWise experts, responded with a blog post that critically reviewed Databricks' findings, reported different results for the same benchmark, and claimed comparable price/performance to Databricks. - Source: dev.to / almost 2 years ago
Snowflake: Snowflake is fast, and works well as a product analytics database. - Source: dev.to / over 2 years ago
If you just go to snowflake.com you can sign up for a demo account for free for a month and I'm fairly certain you can get more than one of these accounts (I would recycle emails doing it all the time.) Once you have an account there's lots of docs and videos out there either using the Database via their UI or via python using their connector. They also have a pyspark connector but you might want to just learn... Source: over 2 years ago
Early stage funding & VCs clearly demarcate between tech companies and tech enabled companies. But, once the PE comes into the picture at the scale of BlackStone, the border between doordash.com and snowflake.com starts to blur. The motivation is to make some bucks by going to IPO and they know how to get it done. Source: over 2 years ago
If you're serious about scaling up, definitely consider Vespa (https://vespa.ai). At serious scale, Vespa will likely knock all the other options out of the park. - Source: Hacker News / 23 days ago
Yahoo released their geographic data catalogue under open license and it still lives on as https://whosonfirst.org/ Afaik https://en.wikipedia.org/wiki/Apache_ZooKeeper started at Yahoo https://vespa.ai/ was Yahoo's search engine for news and other content product, now spinned off (https://techcrunch.com/2023/10/04/yahoo-spins-out-vespa-its-search-tech-into-an-independent-company/). - Source: Hacker News / 3 months ago
I think https://vespa.ai/ has the right approach in this space by focusing on being hybrid - vectors alone aren't great for production use cases, it's the combining of vectors+text that lets you use ranking to get meaningful result. (I'm an investor so I'm biased; but it's also the reason why I invested). - Source: Hacker News / 3 months ago
So what’s the catch? Why is this not everywhere? Because IR is not quite NLP — it hasn’t gone fully mainstream, and a lot of the IR frameworks are, quite frankly, a bit of a pain to work with in-production. Some solid efforts to bridge the gap like Vespa [1] are gathering steam, but it’s not quite there. [1] https://vespa.ai. - Source: Hacker News / 4 months ago
When it comes to search I cannot disagree more. https://vespa.ai is a purpose built search engine. If you start bolting search onto your database, your relevance will be terrible, you'll be rewriting a lot of table stakes tools/features from scratch, and your technical debt will skyrocket. - Source: Hacker News / 10 months ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Meilisearch - Ultra relevant, instant, and typo-tolerant full-text search API
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Typesense - Typo tolerant, delightfully simple, open source search 🔍
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.