Lightening fast data loads done seamlessly!!
April 21, 2022

Lightening fast data loads done seamlessly!!

Samiran Mudgalkar | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with SingleStore (formerly MemSQL)

The most important use case is to load huge files into a distributed database system within a short span of time without having memory and time complexities. Whenever there is a need of transferring data for ETL during the staging phase and data warehousing stage, the load should be transferred without a lot of resource usage. Especially in the cloud space, the lesser we use the resources, the more cost-effective it is.
  • UI design
  • Perfect SQL editor and faster query execution
  • Ease of pipeline creation for data loads
  • Need to have a place to create an admin user for the first information schema database. Because when we log in, we do not have admin access by default to the system.
  • The state of the pipeline is not available if the currently available load is finished, there is extra work to check if all your files in the current load are complete.
  • The Dashboard can be a bit more simplified than having a lot of details.
  • Reduced Data load times
  • Reduced resource utilization in cloud
  • Faster and effective data transfer
The mere speed of data load in SingleStore is phenomenal. That actually does things quite better than any other solutions we have had till now.
Not much explored in this area so would not be able to comment more.

Do you think SingleStore delivers good value for the price?

Yes

Are you happy with SingleStore's feature set?

Yes

Did SingleStore live up to sales and marketing promises?

Yes

Did implementation of SingleStore go as expected?

Yes

Would you buy SingleStore again?

Yes

1. The one place where it is required the most is, during ETL processing where the resource utilisation is optimized and faster data load is achieved.

2. The places where it is not suited are, when the data load is very low and there is not much difference achieved while execution of data loads.