Stardog Enterprise Knowledge Graph Platform

I use Stardog Enterprise Knowledge Graph Platform mostly as the semantic layer to connect and create data models, connecting data from other sources and using SPARQL queries to expose the data to business users.

In the battery manufacturing industry, we have data coming from SAP, manufacturing data, data from the quality department, and data coming from machines directly. Connecting all of them and providing insight to business users or management is really difficult. Stardog Enterprise Knowledge Graph Platform provides a platform where I can use ontology and data models to create, connect the data, and expose it to users. It is also helpful when users are not able to fetch data from connected sources. For example, a quality department staff member wants to know the status of a raw material and the details which are in SAP. Stardog helps us to connect those and expose that data.

Moreover, Stardog Enterprise Knowledge Graph Platform has an advantage for virtualization where it lets us connect directly to our data lake, Databricks. I fetch data directly through SPARQL queries without having to materialize the whole data because the size of data is substantial. Materializing it would be a very difficult task. When it comes to virtualization, it is really helpful to use Stardog Enterprise Knowledge Graph Platform.

Stardog Enterprise Knowledge Graph Platform has positively impacted my organization because I started working with it since Stardog was also developing. Now Stardog has grown significantly. I remember when I started working with Stardog, we were working together. Both entities were growing together. Our organization is also a startup, so hand in hand, we were also improving along with Stardog. Stardog was improving themselves with our use case and learning many things, and I was learning many things as well. I was not a professional in ontology and the semantic layer, but with Stardog, Stardog was my first interface on the semantic world. It was really helpful to learn.

A positive outcome in my organization involved a very important use case for traceability of materials and data for traceability that was really in a state of disorder. Stardog helped us to consolidate, join, and bring the data together and helped us to create the data model. Now I have good traceability for cells from raw material till cell creation and all the data on the way. This has a very positive impact in the industry, not only for now, but for the future also, because it helps from operator to management. Everyone who wants to ask a question about battery manufacturing for a particular battery has all the details on it.

For example, extracting traceability for a cell in our use case in battery manufacturing, the tools which already were in place and to take the traceability out manually from the data took almost 10 to 15 minutes, while from Stardog, after connecting everything, it takes only two minutes. I think that is a quite significant amount of time saved.

According to my use case, I think the best feature of Stardog Enterprise Knowledge Graph Platform is virtualization where it lets me access virtualized data without having to materialize everything in the semantic layer. Moreover, all the features such as Launchpad, provided by Stardog, which gives a perfect user interface to test SPARQL queries and to run the queries, to check the status of the server and everything, is really good.

Virtualization in Stardog Enterprise Knowledge Graph Platform was valuable because I did not want to materialize the whole data. That is where virtualization was really helpful. In the beginning, I was looking for a platform, for a semantic layer, where it could enable me to directly query the data lakehouse without materializing data. I wanted to connect and fetch the data, and Stardog was a perfect fit for my use case.

Launchpad has a clearly different scenario and use case, but it is really helpful when I want to test SPARQL queries. It gives a very simple user interface and is easy to understand. Stardog has three components: Explorer, Designer, and Studio. Studio is mostly helpful for me. Designer has many new features and good features, but I have not explored Designer as much because I was already relying on my self-created ontology. Explorer is also helpful in some scenarios, though it has some drawbacks.

I wish that in Launchpad, there was a feature where I could let users access the features I want them to access. I do not want to give any user the whole access to Launchpad. There are users I do not want them to access Studio, but I want them to have Explorer visible because Explorer is more analytical and it shows structured data in an easy user interface way. Without giving Studio access, if I want some users to access Explorer, it would have been really helpful.

I think Launchpad provided by Stardog Enterprise Knowledge Graph Platform has scope of improvement where more restriction on user management could be available. If someone is in Launchpad, they can access everything. I think that is a good area of improvement. Beyond that, I have been facing some issues with query performance. I do not know how everything is working in the backend, but I think there is scope of improvement in query performance.

Query performance is inconsistent. Sometimes it is performing really well, but the same query sometimes does not perform well. It is really difficult to figure out what the actual root cause is. I think Stardog could help by looking into the backend so that the performance should be consistent. I could expect the performance time or performance metric. That would be really helpful because if some query is taking three minutes, I do not know if it is a good performance or not. Maybe it is supposed to take three minutes. If Stardog could let me know that this should take a certain amount of time, it would be really easy to quantify whether this is not performing well and I can improve from my side or Stardog has to from their side. It would be really easier to understand.

Regarding Stardog Enterprise Knowledge Graph Platform's governance and security, I think the basic governance and security what Stardog is providing is up to the mark. Still, there is scope of improvement. For example, through Launchpad, there is scope of governance for the tools. I do not want to give access to everything to the users through Launchpad. I think many organizations will not want to give access to everything to the users through Launchpad. Through Launchpad, if there would be more governance, more restriction, more control of user management, it would have been great.

Regarding upcoming artificial intelligence capabilities such as Voicebox, I am still exploring it. I got it featured a few weeks back and I am exploring. I would not say I am really satisfied, but the answers which it is providing through artificial intelligence are not really bad. I think there is still scope of improvement there and I am sure because it is new for Stardog also, we both will grow together and it will be improved in the future.

I have been using Stardog Enterprise Knowledge Graph Platform for the last three years since I joined this company.

I would rate Stardog Enterprise Knowledge Graph Platform an eight on a scale of 1 to 10. While I am really happy with how Stardog platform is growing, I still see there is a lot of scope of improvement and as mentioned before regarding the performance of the queries and performance on Launchpad. Because there is a lot of scope of improvement still there, that is the reason I am rating it an eight. The tool is not perfected for all scenarios. Keeping in mind this scope of scenarios, I am giving it an eight.

There is no specific advice regarding Stardog Enterprise Knowledge Graph Platform, but if people are looking for a semantic layer, every industry should look for a semantic layer because it has many use cases and could be useful in many areas. I would advise others to really look into Stardog Enterprise Knowledge Graph Platform. If it can help their use case to resolve some issues, it could be beneficial. Stardog Enterprise Knowledge Graph Platform is a great platform to examine. At minimum, people should try it once. It is worth trying once, and I am sure they will appreciate it and will continue with it.

Stardog Enterprise Knowledge Graph Platform is a knowledge graph platform where we store triples, which are RDF compliant data in the database. In the project, we have a home comfort domain with different appliances. We store all the home comfort data in Stardog Enterprise Knowledge Graph Platform.

One of the features is the LLM-based voice box, which allows you to talk to your database using natural language. This LLM-based feature means you do not need to write all the SPARQL queries, those large queries. When you tell the LLM in natural language what fields and data you need from the triples, you can retrieve it using natural language without writing thousands of lines of query.

I would add information about ontology. In Stardog Enterprise Knowledge Graph Platform, you can create the ontology and the model. The model can now be created with the help of LLM as well. If you want to create a model, you can share the use case, stating the different data such as product, product customers, and sales count. You can give the data in a CSV file and provide the LLM with the use case, and it will create an ontology for you.

Stardog Enterprise Knowledge Graph Platform is highly secure because the answers are not hallucinated. The data comes from your database only, not from the LLM trained data. I am confident that the LLM-based capability of Stardog Enterprise Knowledge Graph Platform is excellent. They have beautifully built these AI capabilities, and they work very well.

I found that some of the documents are not up to date. Sometimes they update the software, but they do not update the documentation on time. This is one of the drawbacks I have seen.

Another software called Neo4j provides some more features compared to Stardog Enterprise Knowledge Graph Platform. That is the reason I have given a lower rating to Stardog Enterprise Knowledge Graph Platform. We have lost a few customers, but now Stardog Enterprise Knowledge Graph Platform has also started offering the ability to scrape entities and relationships from unstructured data, such as PDF and DOC files. This feature was not available earlier, but now they are providing it.

I have been using Stardog Enterprise Knowledge Graph Platform for more than four years.

Stardog Enterprise Knowledge Graph Platform is very stable.

It is very highly scalable. You can store a large amount of data.

The customer service is very good. The only drawback is that they are located in the US right now. Recently, they have opened an office in India during IST hours. They provide very good support.

We have used another graph database platform called Anzo. We had security issues and features issues with Anzo. The main reason was the security, and we had a lot of trouble with it. That led us to move from Anzo. Anzo is from the Cambridge Semantics stack. We moved from Anzo to Stardog Enterprise Knowledge Graph Platform.

The initial setup is very good and cheap. The setup required very little.

We do save money from Stardog Enterprise Knowledge Graph Platform. We have compared between different graph databases, and we found that you can get Stardog Enterprise Knowledge Graph Platform Enterprise license compared to other graph databases for a much lower price.

The pricing is very less compared to other graph databases. For setup cost, all you need is a VM. If you have a VM, you can set up Stardog Enterprise Knowledge Graph Platform easily.

We have evaluated Ontotext GraphDB.

I recommend using the AI capabilities more, as that will help you develop faster and more accurately. Using AI in Stardog Enterprise Knowledge Graph Platform is very useful. I would rate this review an 8 overall.

My main use case for Stardog Enterprise Knowledge Graph Platform was to keep our data in graph format in my previous organization, wherein the entire data model which I used in Power BI included Stardog as one of the data sources. While creating the data model, I was using Stardog Studio to modify or retrieve the actual data that I wanted in my Power BI model. I used to fire SPARQL queries in Stardog so that I could get my result.

A quick, specific example of how I used Stardog Enterprise Knowledge Graph Platform in one of my Power BI projects is that Stardog is considered a very robust platform, a graph platform, which was used in my organization to store graph format data. I used it, and while connecting it with Power BI, I was using an ODBC connector, such as the BI connector that is given with Stardog. That was the method of how I used it.

In my experience with Stardog Enterprise Knowledge Graph Platform, many graph platforms do not have a very user-friendly client experience. What I found was that Stardog Studio had a very rich client experience in which we were able to fire queries and do many things through drag-and-drop functionality. That was one of the best features I found in Stardog.

The rich client experience and drag-and-drop functionality in Stardog Studio made my work easier because my main use case to use Stardog was to retrieve the data which I needed in my Power BI data model. I was using it to fire SPARQL queries and get the exact data that I wanted. One of the best features that I liked was whenever I fire a query, the query runs quicker because I am only getting the top 100 or top 1000 records for my result. If I wanted the full data in my result, I just needed to tweak it a bit and then I would get my full result. The other feature was being able to export that data in any format that I need.

Stardog Enterprise Knowledge Graph Platform has positively impacted my organization since it has been used for more than four to five years, and everyone has been positively affected by the use of it. It was a tool that was used to store our very complex data in the form of data structure, and it was efficiently managed by Stardog.

I don't know what can be improved in Stardog Enterprise Knowledge Graph Platform since I was not working as a main developer in the Stardog team. For me, it was all acceptable when I used Stardog.

Maybe support for Stardog Enterprise Knowledge Graph Platform can be better, but there is nothing else I would mention.

I have been using Stardog Enterprise Knowledge Graph Platform for around two years ago and had been using it till six months ago. That was in my previous role.

In my experience, Stardog Enterprise Knowledge Graph Platform can be stable.

Stardog Enterprise Knowledge Graph Platform handles increasing data volumes well.

There was a difficult scenario when I was first connecting Stardog Enterprise Knowledge Graph Platform with Power BI through ODBC connector, because at that time there was an issue where the actual connector port was not enabled from my client's side. When we asked this particular query to Stardog support team, they were not able to resolve it for months. Around three to four months they were not able to resolve this query, so it was a very difficult task to connect Power BI with Stardog ODBC.

My experience with customer support for Stardog Enterprise Knowledge Graph Platform was a bit weak because the problem that we told Stardog support was very basic, and they were not able to get an answer to that for months. It is considered weak support.

I would rate Stardog Enterprise Knowledge Graph Platform around seven out of ten.

I chose seven out of ten because I have heard from my colleagues who were working on Stardog development that there were some features missing or it could be a bit better. The type of problem that I faced in the support has taken out three points. My overall review rating for Stardog Enterprise Knowledge Graph Platform is seven out of ten.