Azure Cosmos DB

Google Maps lets "property owners and their authorized representatives" upload indoor maps, but this appears to lack navigation ("wayfinding").

MappedIn is a platform and has SDKs for building indoor mapping experiences (https://www.mappedin.com/) and ESRI ArcGIS also offers some indoor mapping tools (https://www.esri.com/en-us/arcgis/indoor-gis/overview). Finally, there used to be a company called LocusLabs that is now a part of Atrius and they were often integrated into airlines' apps to provide airport maps with wayfinding (https://atrius.com/solutions/personal-experiences/personal-wayfinder/).

I previously worked at Mapbox and while I believe that it's a great platform for building map-based experiences, they don't have any simple solutions for indoor wayfinding. If I were doing this for fun as a side-project and prioritized saving money over saving time, here is what I would do:

• Create a graph-based dataset representing the walking paths around your university, where nodes/vertexes represent the intersections of paths, and edges represent paths (literally paths outside, hallways, short path segments that represent entering rooms). You could store this in a hosted graph-based database like Neo4j, Amazon Neptune , or Azure Cosmos DB (with its Gremlin API) and use built-in "shortest path" queries, or deploy a PostgreSQL service with pgRouting.

• Add two properties to each edge: one property for the distance between its nodes (libraries like @turf/helpers will have a distance function if you have the latitude & longitude of each node), and another property estimating the walking time (based on the distance). Once you have these values saved in a graph-based format, you should be able to easily query and find the data representation of paths between two points.

• At this point, you'd have the routing problem solved and it would come down to building a UI. Mapbox arguably leads the industry in developer tools for custom map experiences. You could convert your nodes/edges to GeoJSON, then either upload to Mapbox and create a Tileset to visualize the paths, or add the GeoJSON to the map on the fly.

*You might be able to use open source routing tools like OSRM (https://github.com/Project-OSRM/osrm-backend/issues/6257) or Graphhopper (instead of a custom graph database implementation), but it would likely be more involved to maintain these services.

We are building cloud based analytical app and most of the data for UI is supplied from SQL server to Delta lake and then from Delta Lake to Azure Cosmos DB as JSON using Databricks. So that API can send it to front-end. Sometimes we get larger documents while transforming table rows into JSONs and it exceeds 2mb limit of cosmos size. What is the best solution for replacing Cosmos DB?

Hi Mohamad, out of these two options, I'd recommend starting with MongoDB (on MongoDB Atlas) for a few reasons:

• Open Source & Portability - With MongoDB being open source, you have transparency into how your system will work. Not only can you see how it works, but you later have the option to migrate to self-hosted versions of the platform (decreasing costs and avoiding vendor lock-in) or move to a Mongo-compatible hosted database like Amazon DocumentDB or Azure Cosmos DB.

• Querying & Aggregation - MongoDB has been around a few years longer than Firebase, and in my opinion, that is evident from the great design and flexibility of APIs you have for querying and aggregating data.

• Tooling - MongoDB Atlas monitoring tools and the Compass GUI are great for understanding and interacting with the data in your database as you're growing your platform.

I hope this helps!

We have an in-house build experiment management system. We produce samples as input to the next step, which then could produce 1 sample(1-1) and many samples (1 - many). There are many steps like this. So far, we are tracking genealogy (limited tracking) in the MySQL database, which is becoming hard to trace back to the original material or sample(I can give more details if required). So, we are considering a Graph database. I am requesting advice from the experts.

1. Is a graph database the right choice, or can we manage with RDBMS?
2. If RDBMS, which RDMS, which feature, or which approach could make this manageable or sustainable
3. If Graph database(Neo4j, OrientDB, Azure Cosmos DB, Amazon Neptune, ArangoDB), which one is good, and what are the best practices?

I am sorry that this might be a loaded question.

I am currently using Azure Cosmos DB for our IoT platform and am planning to switch to another #NoSQL database for cost and other related issues. I am also looking for a database that has higher capabilities towards reporting solutions through Power BI or other reporting tools.

Need thoughts of which services to use either Amazon DynamoDB or Azure Cosmos DB. I'm more interested in performance comparision between these tools

I need to publish an API for recommending items based on preferences passed as criteria. The recommendation engine logic relies on shuffling and sorting the items in the list. The list of items is small (<1000), so I was thinking of bringing them into context at startup (singleton pattern), and letting my Azure Functions (or alternative? must be on Microsoft Azure) do the number crunching with direct access to this dataset. Is this viable, and if so, where should I implement my singleton initial load (from file): directly within the Azure Function? If not, what else? Or if the singleton idea doesn't offer much benefit, what good (and cheap) fast-access data store would be recommended? Azure Cosmos DB? Any other? Each of my items can be represented by a small JSON document, like: { "id" : "...", "name" : "...", "description" : "...", "qualifiers" : [ "qualifier" : "...", "qualifier" : "...", "qualifier" : "..."]} (description < 1000 chars; no more than 10 qualifiers).

If you need a document-based database with geo-redundancy (imagine AU-HU distance), this is the way to go. Azure Cosmos DB