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.
N/A
Google Cloud SQL
Score 8.7 out of 10
N/A
Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
$0
per core hour
Pricing
Astra DB, now part of IBM watsonx.data
Google Cloud SQL
Editions & Modules
No answers on this topic
License - Express
$0
per core hour
License - Web
$0.01134
per core hour
Storage - for backups
$.08
per month per GB
HA Storage - for backups
$.08
per month per GB
Storage - HDD storage capacity
$.09
per month per GB
License - Standard
$0.13
per core hour
Storage - SSD storage capacity
$.17
per month per GB
HA Storage - HDD storage capacity
$.18
per month per GB
HA Storage - SSD storage capacity
$.34
per month per GB
License - Enterprise
$0.47
per core hour
Memory
$5.11
per month per GB
HA Memory
$10.22
per month per GB
vCPUs
$30.15
per month per vCPU
HA vCPUs
$60.30
per month per vCPU
Offerings
Pricing Offerings
Astra DB, now part of IBM watsonx.data
Google Cloud SQL
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Pricing varies with editions, engine, and settings, including how much storage, memory, and CPU you provision. Cloud SQL offers per-second billing.
More Pricing Information
Community Pulse
Astra DB, now part of IBM watsonx.data
Google Cloud SQL
Features
Astra DB, now part of IBM watsonx.data
Google Cloud SQL
Vector Database
Comparison of Vector Database features of Product A and Product B
Astra DB, now part of IBM watsonx.data
8.0
12 Ratings
0% below category average
Google Cloud SQL
-
Ratings
Vector Data Connection
8.212 Ratings
00 Ratings
Vector Data Editing
8.56 Ratings
00 Ratings
Attribute Management
7.910 Ratings
00 Ratings
Geospatial Analysis
8.26 Ratings
00 Ratings
Geometric Transformations
8.06 Ratings
00 Ratings
Vector Data Visualization
7.87 Ratings
00 Ratings
Coordinate Reference System Management:
7.86 Ratings
00 Ratings
Data Import/Export
7.811 Ratings
00 Ratings
Symbolization and Styling
8.45 Ratings
00 Ratings
Data Sharing and Collaboration
7.69 Ratings
00 Ratings
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
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.
Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.
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.
As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.
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.
GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.
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++
Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.
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.
Improved integration with Google Cloud, we have set up some automations with Google Workspace, and we have noticed that the raw data sharing between them is very fast as compared to using some other managed database, not sure why.
Due to some downtime during maintenance, we had to set up a relatively small service which ingested the data while this went down and dumped it when it came back up. So this was a negative impact on our ROI, since now we had to remedy this downtime against the same profit margins
It was cheaper than the legacy aws service since we needed large database instances