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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DataStax Enterprise
Score 9.1 out of 10
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DataStax Enterprise (DSE) is the scale-out, cloud-native NoSQL database built on Apache Cassandra. DSE is Developer Ready providing developers the freedom of choice of REST, GraphQL, CQL and JSON/Document APIs.
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Pricing
Astra DB
DataStax Enterprise
Editions & Modules
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Offerings
Pricing Offerings
Astra DB
DataStax Enterprise
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
Astra DB
DataStax Enterprise
Considered Both Products
Astra DB
Verified User
Anonymous
Chose Astra DB
We also (briefly) considered building in-house. We wanted to avoid complex "Frankenstein" architectures. Combining Pinecone with another NoSQL datastore like DynamoDB would have increased complexity. A single-managed platform (Astra DB) enabled architectural simplicity and …
We selected Astra for reducing complexity of our operations, local support, scalability, reliability, and business continuity/contingency planning reasons. We're a small team so prefer a database-as-a-solution model.
Astra DB allowed us running a database without going deep into the configuration hell. It scales with our usage and therefore, there was no need to learn the sepcialities of a vector database.
For the workloads we use Astra DB for it was a better choice than the other databases. It worked out to be more scalable and cost affective than the traditional relational databases. Also performant and without the downsides of size limits compared to other services.
I never tried Pinecone with a production workload, but I can say that the enterprise support and care of DataStax is game changer. They really put effort in creating with you a valid and effective solution for your business.
Astra DB is at par with each one of them as it's scalability and availability is unmatched. The best thing about Astra DB is it's managed service takes care of database operations, freeing up development teams to work on application features. With its scalable architecture and …
Astra DB is a managed database service based on Apache Cassandra that is mostly used for NoSQL data storage and administration, whereas Azure is a full cloud computing platform provided by Microsoft that includes infrastructure, platform, and software services. Astra DB is …
Astra DB, which is built on Apache Cassandra, is well-known for its smooth horizontal scalability, making it an ideal solution for applications with quickly rising data and traffic. Although MongoDB Atlas provides high availability, Astra DB's multi-region capability can …
Since I was familiar with CQL, choosing Astra DB was the only smart choice for me. It is equally capable as all the other cloud-based fully managed database services currently out in the market. It provides very good documentation also for people who are new to it, making it …
Astra DB supports Cassandra which is very important and of key notice. We work on Cassandra , thus we need Astra DB. Astra DB has high availability and scalability. The customer service provided by Astra DB is really helpful and the response is always available. Astra DB has …
Astra DB supports apache cassandra which in itself is a plus point. It's primary database model has a wide column store. Deployment of Astra Db takes minutes in AWS, Google Cloud, Azure. Also it is schema free. It also has advanced replication for edge computing. In other …
The tools astra db provides are much more effective and efficient, especially the integration allowed within astra db. One can customize the choice of tools as per their requirements.
Astra DB has a better database system than Mongo DB and that why me and my team prefers using Astra DB over all the database tools available. The Apache Cassandra database is what attracts the user to Astra DB rather than other databases. Wide Column storing database is what we …
Astra in the general case ends up coming in cheaper than it costs to run your own VMs on a VPS to self-host either cassandra or scylla. How they do that, I don't know, but I'm glad they do!
Some advantages of Cassandra by itself over the other solutions is being masterless and column oriented. About Astra DB, for us the decision-making factor was having a serverless solution and with the latest Cassandra version and features, additionally it provides a rich set …
I have previously used and evaluated MongoDB and MySQL for various projects before choosing AstraDB for my chatbot application. While MongoDB and MySQL are both powerful and popular database solutions, AstraDB stood out for specific reasons in the context of my project.MongoDB, …
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 …
I believe DataStax Enterprise is the best in class. There are some things that are different with the schema-less systems but I found DataStax Enterprise easiest to implement while evaluating. The replication is on par or better than others in practice. We are evaluating …
DataStax Enterprise offered best-in-class write performance and scalability. The customer support team was very helpful in the adoption of new technology.
DataStax has an amazing community built around it and is also Cassandra is an open-source technology. The customer support is quite good compared to other vendors. Though you initially need to spend some hefty amount on infrastructure, in the long run, it makes up for it. We …
We chose datastax because we need a system always available and capable of ingesting a large amount of data per second, even if eventually consistent and with multi data center sync native support.
We considered Cloudera as an alternative using Kafka as the ingestion layer but …
Amazon DynamoDB and Datastax Cassandra are similar on masterless architecture and principles, DynamoDB is managed and needs cost analysis. If you need to have better control, Datastax is better.
I also did a prototype with Google Spanner in one of the recent innovation days, it …
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.
DataStax has a good scalable option with multiple clusters and a good write rate. Cassandra also is improving and is an open-source technology that has good community support. The UI is also easy to understand and implement required functions.
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.
Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.
Astra DB might be difficult to understand for people who are unfamiliar with Apache Cassandra. Improving the initial experience for newcomers, as well as offering better documentation and lessons, might be advantageous.
The Astra DB ecosystem may be enhanced by expanding the ecosystem of plugins, integrations, and community-contributed solutions.
There is a bit of a learning curve and tasks that are simple in traditional RDBMS systems can be complicated with DataStax Enterprise but once you get the hang of denormalizing data and getting the data model correct DataStax Enterprise is very usable. Usability from the developer's standpoint is very simple - the complication is on the architecture side with the data model.
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 had a few situations where we caused an outage or something has gone wrong and we are able to get a support person to offer live help within minutes. The escalation process is excellent - the best I've seen - and the support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through data model exercises and the subscription I believe still comes with some hours to help get the data model reviewed.
We also (briefly) considered building in-house. We wanted to avoid complex "Frankenstein" architectures. Combining Pinecone with another NoSQL datastore like DynamoDB would have increased complexity. A single-managed platform (Astra DB) enabled architectural simplicity and strong reliability, allowing Maester’s development team to prioritize high-value, customer-facing features
I believe DataStax Enterprise is the best in class. There are some things that are different with the schema-less systems but I found DataStax Enterprise easiest to implement while evaluating. The replication is on par or better than others in practice. We are evaluating Astra in our test environment and that has additional benefits we are looking forward to using.
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.
Database growth planning is less of a concern with Astra, as it scales automatically.
Currently, they lack fine-grained security at the table level. I suspect that will change over time.
If your load has peaks and valleys; Astra enables only paying for Reads/Writes; thus you do not need to pay for large servers to support peaks in load.