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A perfect technology partner to build AI applications
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.
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More than a partner
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
Best Vector DB experience we had so far
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
Working on free experimental database for open access, publicly sourced data
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.
Astra DB adoption in Enterprise
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
Astradb for VectorStore
What do you like best about the product?
The astradb for vectorstore and its integration to langchain for ease of orchestration of RAG workflows.
Datstax team is phenomenally talented and supportive to customers.
They are open to consider the feedback for enhancing the latest technologies and integrations.
Datstax team is phenomenally talented and supportive to customers.
They are open to consider the feedback for enhancing the latest technologies and integrations.
What do you dislike about the product?
I like everything about datastax but would like for a more evolved UI interface.
What problems is the product solving and how is that benefiting you?
Datstax is solving us the LLM token limitations and cost effectiveness with RAG-Vector solution.
Go-to database for production grade LLM apps
What do you like best about the product?
Support and robustness.
Astra DB is rock-solid. We experienced a 50x traffic increase on our conversational chatbot "AI Guru" with zero downtime during a live demo with 1 million students. This is a testament to the scale at which AstraDB can deliver in production usecases.
Astra DB is rock-solid. We experienced a 50x traffic increase on our conversational chatbot "AI Guru" with zero downtime during a live demo with 1 million students. This is a testament to the scale at which AstraDB can deliver in production usecases.
What do you dislike about the product?
Data ingestion and retrieval for analytics can be improved. I am hoping it will be a solved problem in the coming months.
What problems is the product solving and how is that benefiting you?
We are using AstraDB as our vector database for our GenAI apps. That includes real-time doubt solving, Counselling and mentoring, subjective paper evaluation.
Datastax : Apache Cassandra advanced in Cloud
What do you like best about the product?
The multiple ways of connection - REST API based operations for create, insert, delete or update , option to use cql and driver based connections, easy to query and great performance are the best feasture of Datastax.
The ease of setp and usage with various languages like java, python and node make it an easy to use database for newer languages
The ease of setp and usage with various languages like java, python and node make it an easy to use database for newer languages
What do you dislike about the product?
Datastax being based out of cassandra has queries based on model objects and so not all columns can be used for where clause which makes it to think the design in advance. The key columns and query columns need to be identified.
Blob data saving example is not present.
Blob data saving example is not present.
What problems is the product solving and how is that benefiting you?
It helps to solve mapping of data to database using rest api and data can be exposed to thrid party using rest api and various role / user permissions. White listing of IPs are present and managing of database is very easy.
The data can be store based on key and the value object which can be complex.
Continuous storage of data and easy rollups help in its usage as monitoring database.
The data can be store based on key and the value object which can be complex.
Continuous storage of data and easy rollups help in its usage as monitoring database.
Company Chatbot in 30 days
What do you like best about the product?
Customer support has been great from day one. DataStax wants you to succeed with your project.
What do you dislike about the product?
Moving and copying databases between accounts and regions is difficult.
What problems is the product solving and how is that benefiting you?
DataStax makes life easy for engineers who need a scalabe vector database for their RAG projects. It outperformed other databases in our tests.
We've gone to zero to production in 3 months. Top notch support from different departments.
What do you like best about the product?
Support
Vector similarity search
Different API availability and support
Vector similarity search
Different API availability and support
What do you dislike about the product?
Documentation is a little lacking but made up up by direct support.
What problems is the product solving and how is that benefiting you?
Integration with AI applications
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