SingleStore aims to enable organizations to scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.
$0.69
per hour
Valentina
Score 7.0 out of 10
N/A
Valentina is a relational database software solution offered by Paradigma Software.
Good for Applications needing instant insights on large, streaming datasets. Applications processing continuous data streams with low latency. When a multi-cloud, high-availability database is required When NOT to Use Small-scale applications with limited budgets Projects that do not require real-time analytics or distributed scaling Teams without experience in distributed databases and HTAP architectures.
If you have to manage a lot of different databases from different vendors, you could do well by standardizing on this product. It checks all the boxes for a proper database management studio. You would only have to learn one product to manage them all. However, if you are looking to find a good product for a single database vendor, you might be better off finding a tool that was designed specifically for that vendor product.
Foreign Key Constraint data viewer! This was a tremendously helpful feature that not many other products have. Just pick a constraint and see the data in the child tables! No setup required!
It does not release a patch to have back porting; it just releases a new version and stops support; it's difficult to keep up to that pace.
Support engineers lack expertise, but they seem to be improving organically.
Lacks enterprise CDC capability: Change data capture (CDC) is a process that tracks and records changes made to data in a database and then delivers those changes to other systems in real time.
For enterprise-level backup & restore capability, we had to implement our model via Velero snapshot backup.
Somewhat laggy performance. Boot up speed was on the slow side and connecting to our database servers was also a little slower than other products.
User interface can be a little clunky. Instead of the usual tree view of servers, databases, and schemas, you are presented with lists that you click on and get new windows to pick the new list of data from. Not organized efficiently.
[Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
SingleStore excels in real-time analytics and low-latency transactions, making it ideal for operational analytics and mixed workloads. Snowflake shines in batch analytics and data warehousing with strong scalability for large datasets. SingleStore offers faster data ingestion and query execution for real-time use cases, while Snowflake is better for complex analytical queries on historical data.
The support deep dives into our most complexed queries and bizarre issues that sometimes only we get comparing to other clients. Our special workload (thousands of Kafka pipelines + high concurrency of queries). The response match to the priority of the request, P1 gets immediate return call. Missing features are treated, they become a client request and being added to the roadmap after internal consideration on all client needs and priority. Bugs are patched quite fast, depends on the impact and feasible temporary workarounds. There is no issue that we haven't got a proper answer, resolution or reasoning
We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
Greenplum is good in handling very large amount of data. Concurrency in Greenplum was a major problem. Features available in SingleStore like Pipelines and in memory features are not available in Greenplum. Gemfire was not scaling well like SingleStore. Support of both Greenplum and Gemfire was not good. Product team did not help us much like the ones in SingleStore who helped us getting started on our first cluster very fast.
Compared to Microsoft's SQL Management Studio, Valentina studio was comparable, just harder to get used to in the UI department. It ran slightly slower than other products but did save some time with neat features they baked into the product. However, in using DBeaver Community and DBForge Studio for PostgreSQL from Devart, we found different products that the team ultimately decided to use. DBeaver has all of the features we needed most (minus the constraint data viewer) and a more intuitive UI that we were used to. DBForge Studio for PostgreSQL has a very standard Windows look and feel and lacks some features, like database/table designers, but makes up for those shortcomings in the much easier filtering and sorting options right in the data grids. You can even write a query and edit the data returned, which is something we don't see in many of these tools. Our team ultimately settled on the developers using DBeaver and the support team that needs data viewing/editing capabilities using DBForge Studio.
As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data.
Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog.
