Astra DB is a vector database for developers. In 2025 Datastax, the developer and supporter of Astra DB, was acquired. Astra DB is now available as a component of the IBM watsonx.data Multicloud offering.
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InfluxDB
Score 8.8 out of 10
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The InfluxDB is a time series database from InfluxData headquartered in San Francisco. As an observability solution, it is designed to provide real-time visibility into stacks, sensors and systems. It is available open source, via the Cloud as a DBaaS option, or through an Enterprise subscription.
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Prometheus
Score 7.9 out of 10
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Prometheus is a service monitoring and time series database, which is open source.
Prometheus was built to monitor CLOUD infrastructure. InfluxDB also has a good design to monitor time series but does not have a design for these demands. InfluxDB would need customization to integrate with Grafana and other third-party solutions. A disadvantage of InfluxDB is …
Highly customized pricing plans to choose from. Lower pricing for the same features compared to competitors. Easy to reach the support team, which provided detailed documentation and helped set up the Prometheus. Monitoring metrics gets very easy after the integration with …
We've been super happy with Astra DB. It's been extremely well-suited for our vector search needs as described in previous responses. With Astra DB’s high-performance vector search, Maester’s AI dynamically optimizes responses in real-time, adapting to new user interactions without requiring costly retraining cycles.
InfluxDB is very good at storing monitoring metrics (e.g. performance data). InfluxDB is not the right choice if you need to store other data types (like plain text, data relations etc.).
This program works from the roots of the problem and creates a professional matrix for each of its users. This will give them more skills and resources to carry out tasks and reduce the difficulties of operating each of the processes of my work, as well as being An ally for the manipulation and operability of all your master data; Prometheus is very easy to recommend since it is a program that fulfills its mission.
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.
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.
Customer Service: since this is an open-source tool, customer service is not that great. Generally, you get all answers to your problems in online forums, but in case you got stuck, nobody will assist you in a channelised manner. You will have to find the way out on your own, and it may become frustrating at times.
More metrics for dashboards shall be added per the application being monitored. Standards metrics will work in most cases but may not in specific applications. Therefore, customised metrics shall be created for some of the industry-standard niche applications.
InfluxDB is a near perfect product for time series database engines. The relatively small list of cons are heavily outweighed by it's ability to just work and be a very flexible and powerful database engine. The community and support provided by the corporation are the only areas I have little experience.
It is usable and one can learn if few people in the team are already using it. It can be difficult to understand at the beginning because of non intuitive UI and syntax of the rules. So, I've gone for 7 points as there is some room for improvement in user interface and rules syntax.
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.
We have worked with the InfluxDB support team a few times so far and it has been positive. Issues submitted are worked on promptly and we have good feedback.
Graph, search, analytics, administration, developer tooling, and monitoring are all incorporated into a single platform by Astra DB. Mongo Db is a self-managed infrastructure. Astra DB has Wide column store and Mongo DB has Document store. The best thing is that Astra DB operates on Java while Mongo DB operates on C++
To be honest, I didn't look at alternatives since InfluxDB performs very well if you can oversee the lack of security and HA features. But for all challenges, there is an easy solution which brings you forward (e.g. read load balancing can be achieved by using a common HTTPS load balancer).
Highly customized pricing plans to choose from. Lower pricing for the same features compared to competitors. Easy to reach the support team, which provided detailed documentation and helped set up the Prometheus. Monitoring metrics gets very easy after the integration with Grafana. It also has a sophisticated alert setting mechanism to ensure we don't miss anything critical.
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.
The ROI mentioned during the purchase has not been achieved, however this could be due to lack of data from our side. 2 years of implementation is too early to calculate and confirm the ROI.
