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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Amazon SageMaker

    Score8.3 out of 10
    N/AAmazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.N/A

    Astra DB

    Score8.2 out of 10
    N/AAstra DB from DataStax is a vector database for developers that need to get accurate Generative AI applications into production, fast.N/A
    Pricing
    Amazon SageMakerAstra DB
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Amazon SageMakerAstra DB
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Amazon SageMakerAstra DB
    Considered Both Products
    Amazon AWS
    No answer on this topic
    DataStax
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    40 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    39 Answers
    Happy with the feature set
    No answers on this topic
    98%
    Happy with the feature set
    39 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    97%
    Lived up to sales and marketing promises
    34 Answers
    Implementation went as expected
    No answers on this topic
    97%
    Implementation went as expected
    38 Answers
    Features
    Amazon SageMakerAstra DB
    Vector Database
    Comparison of Vector Database features of Amazon SageMaker and Astra DB
    Feature
    Amazon SageMaker
    -
    Ratings
    Astra DB
    6.8
    6 Ratings
    0% below category average
    Vector Data Connection00 Ratings8.16 Ratings
    Vector Data Editing00 Ratings6.52 Ratings
    Attribute Management00 Ratings9.13 Ratings
    Geospatial Analysis00 Ratings6.41 Ratings
    Geometric Transformations00 Ratings6.41 Ratings
    Vector Data Visualization00 Ratings6.34 Ratings
    Coordinate Reference System Management:00 Ratings5.52 Ratings
    Data Import/Export00 Ratings6.35 Ratings
    Symbolization and Styling00 Ratings6.41 Ratings
    Data Sharing and Collaboration00 Ratings7.44 Ratings
    Best Alternatives
    Amazon SageMakerAstra DB
    Small Businesses
    Saturn Cloud
    Score7.6 out of 10
    No answers on this topic
    Medium-sized Companies
    DataRobot
    Score8.2 out of 10
    No answers on this topic
    Enterprises
    DataRobot
    Score8.2 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Amazon SageMakerAstra DB
    Likelihood to Recommend
    9.0
    (5 ratings)
    8.2
    (40 ratings)
    Usability
    -
    (0 ratings)
    7.8
    (4 ratings)
    Support Rating
    -
    (0 ratings)
    8.9
    (4 ratings)
    Product Scalability
    -
    (0 ratings)
    8.0
    (38 ratings)
    User Testimonials
    Amazon SageMakerAstra DB
    Likelihood to Recommend
    Amazon AWS
    It allows for one-click processes and for things to be auto checked before they are moved through the process but through the system. It also makes training easy. I am able to train users on the basic fundamentals of the tool and how it is used very easily as it is fully managed on its own which is incredible.
    Incentivized
    Read full review
    DataStax
    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.
    Incentivized
    Read full review
    Pros
    Amazon AWS
    • Machine Learning at scale by deploying huge amount of training data
    • Accelerated data processing for faster outputs and learnings
    • Kubernetes integration for containerized deployments
    • Creating API endpoints for use by technical users
    Incentivized
    Read full review
    DataStax
    • 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.
    Incentivized
    Read full review
    Cons
    Amazon AWS
    • It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
    • Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.
    Incentivized
    Read full review
    DataStax
    • Need better fine-grained Security options.
    • 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.
    Incentivized
    Read full review
    Usability
    Amazon AWS
    No answers on this topic
    DataStax
    It's a great product but suffers with counters. This isn't a deal breaker but lets down what is otherwise a good all round solution
    Incentivized
    Read full review
    Support Rating
    Amazon AWS
    No answers on this topic
    DataStax
    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.
    Incentivized
    Read full review
    Alternatives Considered
    Amazon AWS
    Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.
    Incentivized
    Read full review
    DataStax
    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++
    Incentivized
    Read full review
    Scalability
    Amazon AWS
    No answers on this topic
    DataStax
    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.
    Incentivized
    Read full review
    Return on Investment
    Amazon AWS
    • We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
    • We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
    • For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
    Incentivized
    Read full review
    DataStax
    • Better uptime due to the managed service having no outages
    • Less technical debt because we don't need to worry about upgrading our Cassandra clusters
    • Lower cost on infrastructure as a whole
    • Quick and easy to integrate vector search into our tech stack
    Incentivized
    Read full review
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