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Compare Amazon DynamoDB vs. Amazon Timestream

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3,178 views|2,708 comparisons
Amazon Timestream Logo
1,502 views|1,381 comparisons
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Pricing and Cost Advice
"Its subscription cost is lower than similar databases offered by other vendors."

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Questions from the Community
Top Answer: Its scalability is really good. I can go up to a petabyte of data. It is more of an on-demand use case. I can go from 100 MB to 1 PB if I want, which is very good. Most of the other databases would… more »
Top Answer: Currently, there is no option for a scheduled refresh in this solution. We want the data to be populated into DynamoDB on a timely basis. Currently, you have to go to the DynamoDB table and hit the… more »
Top Answer: I am currently using it for proof of concept and testing out its capabilities. We are publishing the IoT data on DynamoDB. We have its latest version.
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Ranking
Views
3,178
Comparisons
2,708
Reviews
3
Average Words per Review
462
Rating
7.3
Views
1,502
Comparisons
1,381
Reviews
0
Average Words per Review
0
Rating
N/A
Comparisons
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Overview

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. You can use Amazon DynamoDB to create a database table that can store and retrieve any amount of data, and serve any level of request traffic. Amazon DynamoDB automatically spreads the data and traffic for the table over a sufficient number of servers to handle the request capacity specified by the customer and the amount of data stored, while maintaining consistent and fast performance.

Amazon Timestream is a purpose-built time series database service for collecting, storing, and processing time-series data such as server and network logs, sensor data, and industrial telemetry data for IoT and operational applications. Amazon Timestream processes trillions of events per day at one-tenth the cost of relational databases, with up to one thousand times faster query performance than a general-purpose database.

Amazon Timestream efficiently stores and processes time-series data — data that measures how things change over time — by time intervals. As your data grows over time, Timestream’s adaptive query processing engine understands its location and format, making your data simpler and faster to analyze. Timestream also automates rollups, retention, tiering, and compression of data, so you can manage your data at the lowest possible cost. Timestream is serverless, so there are no servers to manage. It manages time-consuming tasks, such as server provisioning, software patching, setup, configuration, and data retention and tiering, freeing you to focus on building your applications.

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Sample Customers
Samsung, Snapchat, Capital One, Expedia, Tinder, Airbnb, Comcast, Lyft, Redfin, Netflix, Adobe
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Top Industries
VISITORS READING REVIEWS
Media Company27%
Comms Service Provider21%
Computer Software Company20%
Energy/Utilities Company5%
VISITORS READING REVIEWS
Media Company28%
Computer Software Company24%
Comms Service Provider23%
Energy/Utilities Company6%

Amazon DynamoDB is ranked 2nd in Managed NoSQL Databases with 3 reviews while Amazon Timestream is ranked 5th in Managed NoSQL Databases. Amazon DynamoDB is rated 7.4, while Amazon Timestream is rated 0.0. The top reviewer of Amazon DynamoDB writes "Good scalability, low subscription cost, and meets our requirements". On the other hand, Amazon DynamoDB is most compared with Microsoft Azure Cosmos DB, Google Cloud Bigtable, Amazon DocumentDB, Amazon Neptune and Oracle NoSQL Database Cloud, whereas Amazon Timestream is most compared with Microsoft Azure Cosmos DB, Google Cloud Bigtable, Oracle NoSQL Database Cloud, Amazon Neptune and Amazon DocumentDB.

See our list of best Managed NoSQL Databases vendors.

We monitor all Managed NoSQL Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.