Amazon Bedrock vs. Astra DB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Bedrock
Score 8.4 out of 10
N/A
Amazon Bedrock offers a way to build and scale generative AI applications with foundation models, providing a developer experience to work with a broad range of FMs from AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon.
$0
Price for 1,000 input or $0.0004 for 1000 output tokens
Astra DB
Score 8.7 out of 10
N/A
Astra DB from DataStax is a vector database for developers that need to get accurate Generative AI applications into production, fast.N/A
Pricing
Amazon BedrockAstra DB
Editions & Modules
Amazon Titan models- Titan Text – Lite
$0.0003
Price for 1,000 input or $0.0004 for 1000 output tokens
Cohere models - Command Light
$0.0003
Price for 1,000 input
Cohere models - Command Light
$0.0006
Price for 1,000 output
Meta model - Llama 2 Chat (13B)
$0.00075
Price for 1,000 input
Meta model - Llama 2 Chat (13B)
$0.001
Price for 1,000 output
Amazon Titan models- Titan Text – Express
$0.0013
Price for 1,000 input tokens or $0.0017 for 1000 output tokens
Cohere models - Command
$0.0015
Price for 1,000 inputtokens
Anthropic models - Claude Instant
$0.00163
Price for 1,000 input tokens
Cohere models - Command
$0.0020
Price for 1,000 output
Anthropic models - Claude Instant
$0.00551
Price for 1,000 output tokens
Anthropic models - Claude
$0.01102
Price for 1,000 input tokens
AI21 models - Jurassic-2 Mid
$0.0125
Price for 1,000 input or output tokens
AI21 models - Jurassic-2 Ultra
$0.0188
Price for 1,000 input or output tokens
Anthropic models - Claude
$0.03268
Price for 1,000 output tokens
Stability AI Model - SDXL1.0
$49.86
per hour (one month commitment)
No answers on this topic
Offerings
Pricing Offerings
Amazon BedrockAstra 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
Features
Amazon BedrockAstra DB
Vector Database
Comparison of Vector Database features of Product A and Product B
Amazon Bedrock
-
Ratings
Astra DB
8.0
12 Ratings
0% above category average
Vector Data Connection00 Ratings8.212 Ratings
Vector Data Editing00 Ratings8.56 Ratings
Attribute Management00 Ratings8.010 Ratings
Geospatial Analysis00 Ratings8.26 Ratings
Geometric Transformations00 Ratings8.06 Ratings
Vector Data Visualization00 Ratings7.67 Ratings
Coordinate Reference System Management:00 Ratings7.76 Ratings
Data Import/Export00 Ratings7.711 Ratings
Symbolization and Styling00 Ratings8.45 Ratings
Data Sharing and Collaboration00 Ratings7.69 Ratings
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User Ratings
Amazon BedrockAstra DB
Likelihood to Recommend
-
(0 ratings)
8.5
(46 ratings)
Usability
-
(0 ratings)
7.8
(4 ratings)
Support Rating
-
(0 ratings)
8.9
(4 ratings)
Product Scalability
-
(0 ratings)
8.4
(44 ratings)
User Testimonials
Amazon BedrockAstra DB
Likelihood to Recommend
Amazon AWS
No answers on this topic
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.
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Pros
Amazon AWS
No answers on this topic
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.
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Cons
Amazon AWS
No answers on this topic
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.
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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
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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.
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Alternatives Considered
Amazon AWS
No answers on this topic
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++
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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.
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Return on Investment
Amazon AWS
No answers on this topic
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
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ScreenShots