Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application.
Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less.
Qrvey’s multi-tenant data lake includes:
Qrvey’s embedded visualizations support everything from: - Standard dashboards and templates - Self-service reporting - User-level personalization - Individual dataset creation - Data-driven workflow automation
Qrvey delivers this as a self-hosted package for cloud environments. This offers the best security as your data never leaves your environment while offering a better analytics experience to users.
The result: Less time and money on analytics.
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Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies
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Qrvey takes a different approach to embedded analytics. Instead of focusing almost completely on the front end, we know that any analytics function starts with data.
Qrvey includes a full-featured data lake powered by Elasticsearch, not a basic relational caching layer. Furthermore, by including a data lake, the cost to scale out is much less than traditional data warehouses.
For the user-facing components of the platform, Qrvey offers more embedded components and APIs to personalize the experience beyond static dashboards. Qrvey offers:
All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple.
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Customers choose Qrvey for the following reasons:
Based on our record, SQLite seems to be a lot more popular than Qrvey. While we know about 18 links to SQLite, we've tracked only 1 mention of Qrvey. 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.
Since you're on AWS already, check out https://qrvey.com. Source: 6 months ago
Yes. A Lightroom catalog file is, after all, just a SQLite database. (Srsly, make a copy of your catalog file, rename it whatever.sqlite and use your favorite SQLite GUI to rip it open and look at the tables and fields). It's just storing the pathame to the RAW file for that file's record in the database. Source: about 1 year ago
I use visidata with a playback script I recorded to open the sheet to a specific Excel tab, add a column, save the sheet as a csv file. Then I have a sqlite script that takes the csv file and puts it in a database, partitioned by monthYear. Source: about 1 year ago
Use the most-used database in the world: https://sqlite.org/index.html. Source: over 1 year ago
With this in mind, I wrote a few versions of this post, but I hated them all. Then I realized that jodliterate PDF documents mostly do what I want. So, instead of rewriting MirrorXref.pdf, I will make a few comments about jodliterate group documents in general. If you're interested in using SQLite with J, download the self-contained GitHub files MirrorXref.ijs and MirrorXref.pdf and have a look. - Source: dev.to / almost 2 years ago
SQLite, by many estimates, is the most widely deployed SQL database system on Earth. It's everywhere. It's in your phone, your laptop, your cameras, your car, your cloud, and your breakfast cereal. SQLite's global triumph is a gratifying testament to the virtues of technical excellence and the philosophy of "less is more.". - Source: dev.to / almost 2 years ago
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