Astra DB, now part of IBM watsonx.data Reviews and Ratings

Rating: 8.7 out of 10

Score

8.7 out of 10

Reviews

46 Reviews

Agility as a Competitive Advantage

Rating: 10 out of 10

Incentivized

August 12, 2025

Use Cases and Deployment Scope

It all comes down to how fast we can deliver value to our customers. Too often, great ideas are held back by technical limitations or the time it takes to build a scalable tech foundation. That’s why solutions like DataStax Astra DB catch my attention. Having a platform that provides a high-performance, globally scalable database within minutes completely changes the game. It gives product and engineering teams the freedom to test hypotheses, iterate quickly, and scale with agility, something that not long ago seemed out of reach. Technology serving business strategy.

Pros

Deliver value to our customers.
High-performance
Globally scalable database

Likelihood to Recommend

Verified User

C-Level Executive in Information Technology (51-200 employees)

Vetted Review

1 year of experience

By leveraging DataStax Astra DB wealthAPI transformed how it processes transaction data at scale

Rating: 10 out of 10

Incentivized

July 22, 2025

Use Cases and Deployment Scope

To store and search vectors efficiently, we use DataStax Astra DB. This database is specifically designed to process large amounts of data at high speed. It allows us to quickly find and group similar transactions. Astra DB is like a state-of-the-art library where every book (in our case: every vector) has a unique place and can be found quickly.

Pros

Astra DB ensures that the entire process is scalable and responsive
Strict data security measures are also observed
Astra DB enables us to process large amounts of data while performing highly accurate similarity searches

Likelihood to Recommend

We process thousands of transactions every day. To meet this high data load, we needed a database that is both fast and flexible. Astra DB, based on Apache Cassandra, fully meets these requirements and can also be integrated into AI workflows. Astra DB enables us to process large amounts of data while performing highly accurate similarity searches.

Verified User

C-Level Executive in Marketing (11-50 employees)

Vetted Review

2 years of experience

Astra DB - great for fluctuating workloads and consistently fast

Rating: 9 out of 10

Incentivized

July 18, 2025

Use Cases and Deployment Scope

We use Astra DB as the primary data store for our Enrich and Engage products. Enrich is an AI-driven financial transaction enrichment product composed of several models that identify valuable information from data provided either by core banking or digital banking platforms used by financial institutions or retrieved using open banking connectivity. Engage is a set of tools that help financial institutions improve their digital channels with a focus on financial literacy, financial management and making better decisions based on enriched data.

Pros

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.

Cons

We feel that some monitoring/observability improvements could be made - we have lots of different data streams in multiple regions, and being able to monitor consistently across all (incl. the storage) makes life easier.
As with any solution deployed at a large scale, cost is always a major factor

Likelihood to Recommend

It excels at providing Google Cloud-based enterprise storage that scales nicely, is able to handle variable loads and is fast. The critically important part for us - the fluctuating loads - is handled particularly well, and it is not something we would like to handle by sizing the infrastructure towards the peaks, as it would make it prohibitively expensive using some of the potential alternatives.

Verified User

Vice-President in Product Management (51-200 employees)

Vetted Review

3 years of experience

Astra DB carrying out customers work further

Rating: 9 out of 10

Incentivized

July 17, 2025

Use Cases and Deployment Scope

Core in our Legal work assistant application used by thousands of lawyers. Used to be able to work with large context which is crucial in legal work, consisting of factual information and legal sources that need different ways of handling,. Also lawyers need to see the different type of information in relation to create final deliverables that are grounded in the context information.

Pros

Handles many documents
Accurate in retrieval
Fast

Cons

Relevance on specific criteria
More speed
Evaluation functionality

Likelihood to Recommend

-explore large documents

-explore many documents

-explore legal databases

- structure information to be used in legal work

- extracting information for timelines

Knut-Magnar Aanestad

Legal process engineer in Product Management at Saga (11-50 employees)

Vetted Review

2 years of experience

Astra DB Handles Your RAG AI Needs

Rating: 10 out of 10

Incentivized

July 17, 2025

Use Cases and Deployment Scope

We use Astra DB to store vectorized data from all of our company's unstructured files. This allows us to query these documents similar to how we query our structured SQL databases. One use case is the storage of vector data for all documents used in secure data rooms that typically contain hundreds of documents. It allows us to provide our investors with the ability to ask questions about the documents without opening each one. This saves them time and leads to a better customer experience.

Pros

API is straightforward and simple to use
Astra DB Dashboard is simple and easy to understand
The vectorize functionality simplifies the document embedding process
The document querying process is really good at extracting the necessary embeddings to send to an LLM

Cons

In some cases, the Astra Dashboard could be more intuitive, especially when creating new collections and assigning an embedding LLM

Likelihood to Recommend

Astra DB is perfect for RAG AI business use cases. It abstracts out the difficult aspects of vectorization so, as a business, we can focus on the functionality surrounding it instead of the highly technical aspects of vectors.

Rick Atkinson

CTO in Finance and Accounting at Bay Point (11-50 employees)

Vetted Review

1 year of experience

Astra DB made it easier to focus on driving customer value

Rating: 10 out of 10

Incentivized

April 3, 2025

Use Cases and Deployment Scope

Maester leverages Astra DB’s advanced vector search and retrieval capabilities to create an adaptive AI system that continuously refines its responses based on real-world user interactions. Maester also relies on Astra’s performance for semantic clustering. Maester can suggest relevant prompts and related analyses by grouping semantically similar user queries. This approach improves user experience and drives feature adoption, highlighting capabilities such as advanced forecasting and custom financial reporting.

Pros

Superior Vector Search and Performance
Unified Architecture
Hands-On Developer Support
Low Latency & High Throughput

Likelihood to Recommend

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.

Verified User

C-Level Executive (1-10 employees)

Vetted Review

2 years of experience

Astra DB As A Graph Database

Rating: 8 out of 10

Incentivized

September 23, 2024

Use Cases and Deployment Scope

We use Astra DB to enable our Graph Database functionality. This graph database is the core of our e-commerce delivery planning and execution systems. This system enables the business to provide accurate ETAs to customers. It also enables the business to grow our national delivery network simply via configuration. Routes and their capabilities are individually configured to account for the network capacity and courier capabilities around different geographic areas.

Pros

Migration
API Integration
Visibility
Support

Cons

Support - Turnaround time was slow.

Likelihood to Recommend

Anyone looking for a hosted solution of Cassandra DB will find a good offering with AstraDB. It provides the scalability of Cassandra with added security, permissions and visibility. As a user you forget there is a cluster behind the scenes.

Verified User

Manager in Engineering (1001-5000 employees)

Vetted Review

1 year of experience

At any scale, Likely to recommend Astra DB

Rating: 6 out of 10

Incentivized

September 23, 2024

Use Cases and Deployment Scope

Astra DB had helped us in building our indigenous algo for social audio consumption for one of the most dynamic digital consumption markets in the entire world. We started with a problem statement that did not have an existing inspiration and hence it was as as abstract it can get. Astra DB helped us quickly get into a solid ground

Pros

Speed
Accuracy
Cost

Cons

Customisation
Better support
More product offerings

Likelihood to Recommend

The vector database offering from Astra DB forms the core of our algorithm and the computational speed is satisfying for our current, low scale. Will be happy to reccomend if the speed can be witnessed when we grow to 10X of the current scale

Verified User

C-Level Executive in Product Management (11-50 employees)

Vetted Review

1 year of experience

Astra DB (serverless) as primary database for a edtech SaaS product

Rating: 10 out of 10

Incentivized

September 23, 2024

Use Cases and Deployment Scope

We use Astra DB as the database for our OB3 web application, which is used by Higher Education organisations and Universities in Australia and New Zealand. It is therefore one of the core technologies we and our customers rely on for delivery of our service. Our product brings course content and discussions together in online collaborative documents, to enable teacher-led and student-led learning activities. It is delivered integrated with enterprise learning management systems such as Canvas and Blackboard.

Pros

scalability
reliability
local support and technical advice
innovation
monitoring

Cons

portal access to custom backup policies ( but these are coming soon to Azure)

Likelihood to Recommend

We are coming to Astra DB from a background of having used and relied on Cassandra (open source) database for over 10 years. Our use case is particularly well suited to NoSQL. We selected Datastax Astra primarily for scalability, support, contingency planning, and reducing the technical complexity of our operations. We were looking for a reliable partner with strong presence in our region (APAC) and we are confident we've found this in Datastax.

Rodney Tamblyn

Co-founer in Information Technology at OB3 (1-10 employees)

Vetted Review

1 year of experience

View profile

Astra DB Review

Rating: 10 out of 10

Incentivized

September 23, 2024

Pros

Vector Search for AI-Driven Recommendations.
Astra DB is cloud-native, deployment and management are simplified.
Astra DB comes equipped with robust developer tools, including CQL (Cassandra Query Language), REST APIs, and GraphQL support.
Astra DB's Storage Attached Index(SAI) allows for efficient indexing directly on disk, making it much easier to perform complex queries across large datasets

Likelihood to Recommend

For vector search capabilities where you need some powerful querying capability like CQL, Astra DB is the solution. Also Astra DB suits well where someone wants to build a RAG setup. Its cloud-native design and distributed architecture make Astra DB a great fit for companies operating across multiple regions or requiring high availability.

Muhammed Shabeer

Senior Software Engineer in Engineering at Arré (U Digital Content Pvt Ltd) (11-50 employees)

Vetted Review

1 year of experience

View profile

Loading Reviews List....

Home
,
Vector Databases
,
Astra DB, now part of IBM watsonx.data
,
Reviews and Ratings

Astra DB - great for fluctuating workloads and consistently fast

Rating: 9 out of 10

Incentivized

July 18, 2025

Use Cases and Deployment Scope

Pros

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.

Cons

We feel that some monitoring/observability improvements could be made - we have lots of different data streams in multiple regions, and being able to monitor consistently across all (incl. the storage) makes life easier.
As with any solution deployed at a large scale, cost is always a major factor

Likelihood to Recommend

Verified User

Vice-President in Product Management (51-200 employees)

Vetted Review

3 years of experience