Neo4j

I'm evaluating the use of RedisGraph vs Microsoft SQL Server 2019 graph features to build a social graph. One of the key criteria is high availability and cross data center replication of data. While Neo4j is a much-matured solution in general, I'm not accounting for it due to the cost & introduction of a new stack in the ecosystem. Also, due to the nature of data & org policies, using a cloud-based solution won't be a viable choice.

We currently use Redis as a cache & SQL server 2019 as RDBMS.

I'm inclining towards SQL server 2019 graph as we already use SQL server extensively as relational database & have all the HA and cross data center replication setup readily available. I still need to evaluate if it fulfills our need as a graph DB though, I also learned that SQL server 2019 is still a new player in the market and attempts to fit a graph-like query on top of a relational model (with node and edge tables). RedisGraph seems very promising. However, I'm not totally sure about HA, Graph data backup, cross-data center support.

Hey people!!!!! I am developing an application for which graph databases are perfect, but I am low on cash(0 actually), and I am wondering if there is any free service is available for Amazon Neptune or Neo4j or any other substitute is available for the two. As far as I checked, I couldn't find any free service.

Hello Stackshare. I'm currently doing some research on real-time reporting and analytics architectures. We have a use case where 1million+ records of users, 4million+ activities, and messages that we want to report against. The start was to present it directly from MySQL, which didn't go well and puts a heavy load on the database. Anybody can suggest something where we feed the data and can report in realtime? Read some articles about ElasticSearch and Kafka https://medium.com/@D11Engg/building-scalable-real-time-analytics-alerting-and-anomaly-detection-architecture-at-dream11-e20edec91d33 EDIT: also considering Neo4j

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 want to build learning paths in a simple way and visualize them, the way Neo4j or D3.js do it. Example: I have a set of learning resources that can be connected depending on certain criteria. Thus, it would be possible for learners to start from various starting points and have learning paths depending on this starting point.

Following this, I need two things: first, a UI that lets me connect entries from a database so that a linear view, like a path, comes out. And second, a bird's eye view on the various paths like a force-directed graph that stems from the linear connections I made.