Sold by: DataStax, Inc.
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DataStax delivers the real-time vector data that Gen AI apps need, with seamless integration to AWS.
Sold by: DataStax, Inc.
Overview
Astra DB from DataStax is the vector database for developers that need to get accurate Generative AI applications into production, fast.
Astra DB gives you elegant APIs, powerful data pipelines and complete ecosystem integrations to quickly build Gen AI applications on your real-time data for more accurate AI that you can deploy in production.
Built on Apache Cassandra, Astra DB is the only vector database that can make vector updates immediately available to applications and scale to the largest real-time data and streaming workloads, securely on AWS.
Astra DB delivers:
- Up to 18% more relevant vector search results
- 8X to 15X higher throughput
- Request responses to up to 12X faster
- Ultra low latency on billions of vectors
Powered by Apache Cassandra, Astra DB makes all data, including vectors, available immediately with ZERO delay.
Highlights
- Up to 18% more relevant vector search results and 8X to 15X higher throughput
- Request responses to up to 12X faster and ultra low latency on billions of vectors
- For custom pricing and annual commitments, please contact cloud@datastax.com
Details
Features and programs
Financing for AWS Marketplace purchases
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Pricing
Free trial
Try this product free according to the free trial terms set by the vendor.
Pricing is based on contract duration. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for any usage exceeds the entitle amount or not covered in the contract. These charges will be applied on top of the contract price. If you choose not to renew or replace your contract before it ends, access to your entitlements will expire.
Dimension | Description | Cost/month |
|---|---|---|
Astra DB - pay as you go | Astra DB - pay as you go - based on consumption | $0.00 |
The following dimensions are not included in the contract terms, which will be charged based on your usage.
Dimension | Description | Cost/unit |
|---|---|---|
Astra Credits | .01 Astra Credits for $.01 | $0.01 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
DataStax Astra DB includes 1 free 'Standard' support ticket at no additional cost with an option to upgrade to 'Standard' support with an 8 hour SLA. The same engineers that brought you Astra DB will help you throughout your entire application lifecycle. You can ask Astra and Cassandra experts any number of questions, and they will be with you 24 x 365, globally to help you in your journey. If you require higher support SLA's, please reach out to support@datastax.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Marius N.
A perfect technology partner to build AI applications
Reviewed on Oct 28, 2024
Review provided by G2
What do you like best about the product?
Astra's Vector capabilites is one of the foundations of our product. From vectorising product catalogues and partner data to searching complex queries, in real-time, on unstructured data, it's an incredibly powerful tool.
When working with larger brands it's imperative that we're enterprise-ready, that our models are fully customizable and can be hosted in partner environments - something which DataStax allows us to do.
Finally, the team at DataStax are just awesome. They have been supportive from day 1, supporting us from MVP to enterprise-ready software. The team do an amazing job at ensuring the tech is up to date and providing us with great support whenever we need it.
When working with larger brands it's imperative that we're enterprise-ready, that our models are fully customizable and can be hosted in partner environments - something which DataStax allows us to do.
Finally, the team at DataStax are just awesome. They have been supportive from day 1, supporting us from MVP to enterprise-ready software. The team do an amazing job at ensuring the tech is up to date and providing us with great support whenever we need it.
What do you dislike about the product?
There isn't much to dislike about DataStax. The team and product is brilliant.
What problems is the product solving and how is that benefiting you?
Vexctorising unstructured data and providing large customers with an enterprise-ready solution.
Leave a comment0 comments
💎Gianni M.
More than a partner
Reviewed on Oct 24, 2024
Review provided by G2
What do you like best about the product?
I started using AstraDB because it was mentioned as one of the options available to implement memory in Langchain.
The implementation was straightforward and it's worked seamesly from day one.
In the DataStrax team I found a reliable partner and they helped me to find solutions when I was stuck in the process, advicing and using their experience and experties to our service.
The implementation was straightforward and it's worked seamesly from day one.
In the DataStrax team I found a reliable partner and they helped me to find solutions when I was stuck in the process, advicing and using their experience and experties to our service.
What do you dislike about the product?
Honestly nothing. Even when my requests were outside their main experities, they found a way to be supportive.
What problems is the product solving and how is that benefiting you?
Storing conversation for a GenAI application
Mert D.
Best Vector DB experience we had so far
Reviewed on Oct 09, 2024
Review provided by G2
What do you like best about the product?
Fast, easy, responsive team that will help out with issues
What do you dislike about the product?
abstractions can be made better but it would take away flexibility so I understand the current design choices
What problems is the product solving and how is that benefiting you?
Solves RAG pipelines and storage for vectorising data
Jonathan F.
Working on free experimental database for open access, publicly sourced data
Reviewed on Aug 17, 2024
Review provided by G2
What do you like best about the product?
The team has been in close contact throughout the process, providing tutorials and answers that helped us understand the expectations and processes.
The benefits have been customer support
The benefits have been customer support
What do you dislike about the product?
The tutorials often do not match my needs. I needed specific details to use the APIs in a format that did not match my expectations or possibly my needs. I am able to build apps that upload our data to DataStax. But I am unable to access the vector search parameters because the method that I used to upload the data is not the preferred method to query the database. In order to use the tutorials for querying the database, we would have to completely start from scratch with uploading the dataset using the same tutorials. Unfortunately, those tutorials are not set up in a manner that I understand how to upload the data. As such, I find that I might have to build my own database query pipeline
This is a problem for ease of use, ease of integration, ease of implementation
This is a problem for ease of use, ease of integration, ease of implementation
What problems is the product solving and how is that benefiting you?
We are starting a new, free experiment with DataStax to provide Wikidata's data to the world via a DataStax vector database.
We are new to the process of vectorising our data. DataStax has been very helpful in assisting us to build the database and understand the implementation of a vectorised database for integrating our data.
We are new to the process of vectorising our data. DataStax has been very helpful in assisting us to build the database and understand the implementation of a vectorised database for integrating our data.
SP (Saladi Pullaya) N.
Astra DB adoption in Enterprise
Reviewed on Aug 13, 2024
Review provided by G2
What do you like best about the product?
Datastax was able to provide enterprise class product for an Open Source project Apache Cassandra. It is continuing to contribute to open source project. Datastax provides multiple offerings of Cassandra - Dedicated On prem model, Managed Service and Pay per use model.
While migrating from Self managed to Datstax Astra DB, it was ease of implementation that made migration super successful. On going improvements to the product with its roadmap is great to work with
While migrating from Self managed to Datstax Astra DB, it was ease of implementation that made migration super successful. On going improvements to the product with its roadmap is great to work with
What do you dislike about the product?
Datastax Enterprise Support is still not completely matured, it is still work in progress.
What problems is the product solving and how is that benefiting you?
We wanted to address two problems - Ongoing maintenance of clusters and high cost associated with Self managed Apache Cassandra clusters. By migrating to Astra DB Database as Service pay per use model, we are able to solve both the problems effectively