Astra DB from DataStax is a vector database for developers that need to get accurate Generative AI applications into production, fast.
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SingleStore
Score 9.8 out of 10
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SingleStore aims to deliver the world’s fastest distributed SQL database for data-intensive applications: SingleStoreDB, which combines transactional + analytical workloads in a single platform.
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.
SingleStore HTAP engine is well suited for real-time analytics, fast ingestion, scaling OLTP system like MySQL. When you need to run reports or perform aggregates on billions of rows and you get result in seconds, you cannot get this experience with other OLTP engines. I wish DBtLab was a little more developer and supported for SingleStore. This would allow to perform better data transformation. You can use stored procedures, but DBTLabs has become a standard for dimensional modeling in data warehousing projects. This is probably why SingleStore has trouble piercing in the data warehouse world. It is definately capable to compete with Snowflake when it comes to scalability, query performance, data compression, but Snowflake has ravaged the data warehouse market in few years and large corporations have already invested lots of money in migrating into Snowflake. The SingleStore community needs to grow. Everyone who uses SingleStore loves it.
The support team sometimes requires the escalate button pressed on tickets, to get timely responses. I will say, once the ticket is escalated, action is taken.
They require better documentation on the migration of data. The three primary methods for migrating large data volumes are bulk, Cassandra Data Migrator, and ZDM (Zero Downtime Migration Utility). Over time I have become very familiar will all three of these methods; however, through working with the Services team and the support team, it seemed like we were breaking new ground. I feel if the utilities were better documented and included some examples and/or use cases from large data migrations; this process would have been easier. One lesson learned is you likely need to migrate your application servers to the same cloud provider you host Astra on; otherwise, the latency is too large for latency-sensitive applications.
We wish the product had better support for High Availability of the aggregator. Currently the indexes generated by the two different aggregators are not in the same sequential space and so our apps have more burden to deal with HA.
More tools for debugging issues such as high memory usage would be good.
The price was the one that kept us away from purchasing for the first few years. Now we are able to afford due to a promotion that gives it at 25% of the list price. Not sure if we'll continue after the promotion offer expires in another 2 years.
[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's performance is incredible. Our predictive algorithms went from taking 24-48 HOURS down to 15 minutes allowing our team to run those much more frequently. Previously, we were limited to about 60 requests per minute due to table locks. Implementing columnstore on SingleStore allowed us to receive 1000 requests per minute.
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.
Very responsive to trouble tickets - Often, I think, the SingleStore's monitoring systems have already alerted the engineers by the time I get around to writing a ticket (about 10 - 20 mins after we see a problem). I feel like things are escalated nicely and SingleStore takes resolving trouble tickets seriously. Also SingleStore follows up after incidents to with a post mortem and actionable takaways to improve the product. Very satisfied here.
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.
We know Astra is built on Cassandra / Kubernetes / Stargate and can work on any cloud. The competitors we reviewed are cloud specific and create a lock in. We also have the option to run Cassandra / Stargate ourselves if we wanted to. The competitors don’t give that option
Timescale was the biggest alternative option we looked at for SingleStore, however the requirement to learn a new syntax (due to not being SQL compatible) was our biggest pain point. Supporting a new language would require alterations to the Laravel framework, as this only offered SQL integration out of the box. This alteration would be time consuming and would limit our scope to future hiring due to the new syntax.
As per my experience, I never faced issues of scalability with Astra DB. We don't have at the moment a use case with millions of requests or users, so I can't give full score because of my limited use case.
The high availability capabilities of Astra DB can assist in reducing downtime, which is crucial for revenue-generating applications.
The developer-friendly features of Astra DB, as well as support for known query languages, can help expedite development, save development time, and minimize labor costs. This can result in a shorter time to market and a higher ROI.
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.
