DataRobot vs. Astra DB

DataRobot can be used for risk assessment, such as predicting the likelihood of loan default. It can handle both classification and regression tasks effectively. It relies on historical data for model training. If you have limited historical data or the data quality is poor, it may not be the best choice as it requires a sufficient amount of high-quality data for accurate model building.

Incentivized

We use Astra DB to improve our management systems. Storing data has become hassle-free and quite simple. When launching a Cassandra-based cloud application, Astra DB is exactly what you need. In addition to the standard training programs and videos, the extended support and training require significant additional effort to activate and cover which I feel is a bit more tedious task.

Incentivized

• The breadth of models available to use is helpful and allows much more analytical power than programming them all yourself.
• The built-in variable diagnostics are helpful when testing large variable sets to see which perform the best.
• Many of the adjustments on the models are easy to use/it's easy to re-run and kick off new models as you want to try new things.

Incentivized

• We need to be able to process a lot of data (our biggest clients process hundreds of milions of transactions every month). However, it is not only the amount of data, it is also an unpredictable patterns with spikes occuring at different points of time - something athat Astra is great at.
• Our processing needs to be extremaly fast. Some of our clients use our enrichment in a synchronous way, meaning that any delay in processing is holding up the whole transaction lifecycle and can have a major impact on the client. Astra is very fast.
• A close collaboration with GCP makes our life very easy. All of our technology sits in Google Cloud, so having Astra in there makes it a no-brainer solution for us.

Incentivized

• Further improvements to their text analysis tool, to be more like the Qualtrics text analysis tool, would be a great addition. Qualtrics has templates built into their text analysis tool for customer service, quality control, etc, and will automatically slot your text responses into categories associated with certain sub areas of those larger categories.

Incentivized

• Astra DB might be difficult to understand for people who are unfamiliar with Apache Cassandra. Improving the initial experience for newcomers, as well as offering better documentation and lessons, might be advantageous.
• The Astra DB ecosystem may be enhanced by expanding the ecosystem of plugins, integrations, and community-contributed solutions.

Incentivized

DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.

Incentivized

It's a great product but suffers with counters. This isn't a deal breaker but lets down what is otherwise a good all round solution

Incentivized

As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.

Incentivized

Their response time is fast, in case you do not contact them during business hours, they give a very good follow-up to your case. They also facilitate video calls if necessary for debugging.

Incentivized

I've done machine learning through python before, however having to code and test each model individually was very time consuming and required a lot of expertise. The data Robot approach, is an excellent way of getting to a well placed starting point. You can then pick up the model from there and fine tune further if you need.

Incentivized

We also (briefly) considered building in-house. We wanted to avoid complex "Frankenstein" architectures. Combining Pinecone with another NoSQL datastore like DynamoDB would have increased complexity. A single-managed platform (Astra DB) enabled architectural simplicity and strong reliability, allowing Maester’s development team to prioritize high-value, customer-facing features

Incentivized

We are well aware of the Cassandra architecture and familiar with the open source tooling that Datastax provides the industry (K8sSandra / Stargate) to scale Cassandra on Kubernetes.

Having prior knowledge of Cassandra / Kubernetes means we know that under the hood Astra is built on infinitely scalable technologies. We trust that the foundations that Astra is built on will scale so we know Astra will scale.

Incentivized

• We have been able to cut costs by not buying leads that we will not be able to sell on
• We have been able to deploy loan eligibility reporting which brought in new business
• We have been able to improve the performance of our credit providers and our partners which has helped to retain business

Incentivized

• Database growth planning is less of a concern with Astra, as it scales automatically.
• Currently, they lack fine-grained security at the table level. I suspect that will change over time.
• If your load has peaks and valleys; Astra enables only paying for Reads/Writes; thus you do not need to pay for large servers to support peaks in load.

Incentivized