I love how flexible the product is and how it does everything I need. If I have any questions, the staff are quick to response & highly knowledgeable about every aspect of the platform.

Knowi is a good tool to glue together different data sources and be able to query them in a more intuitive way. I'd recommend them slightly earlier than scaling stage where you plan on having much more data to analyze over the course of the following months. Their mongodb integration is powerful and I like the fact that they normalize querying across different data sources. It does take effort/time to integrate into their ecosystem, but their support and account management team is very flexible in providing you with resourcing to get integrated and started. They have a slack community that you can join to get answers and learn from others. TLDR; They are one of the only tools that intuitively support MongoDb. Their support and account management is really amazing - they do care and show it by dedicating their resourcing when you need it most regardless of whether you're a startup or a big client. This by far makes it easier to leverage and get the most out of their ecosystem. Once you pick up their query language, it saves time in getting insights across many different data sources.

Knowi fits within a spectrum of functionality, ease of use, and performance. - Functionality: Knowi provides the ability to query multiple data sources, join data from multiple sources, and perform post-data-retrieval transformations, queries and aggregations; making it more powerful than a native data store client such as Kibana - Ease of Use: Knowi provides drag-and-drop capabilities, visualization and text-based editors for filters and joins, and easy-to-use dashboards and widgets, making it easier to use, quicker to query and visualize data and, ultimately, answer data-based questions, compared to lower-level data science tools such as Spark. Knowi also has a well-established model separating data sources, queries, datasets, and widgets, allowing the lower-level entities (data sources, queries) to be quickly re-used to create additional higher-level entities and answer further questions. The sharing model allows sharing and collaboration of any entity type with other Knowi users and groups. There are multiple options to export and share data and visualizations outside of Knowi as well, including PDF exports and downloads, email, webhooks, etc. - Performance: Knowi's concept of indirect queries and their elastic-store allows datasets to be cached and refreshed at configurable periods, cutting down on, not only query and data visualization times but, load on your backend data stores as well.