Amazon Timestream is purpose-built for time-series data, which makes it far more efficient than traditional relational databases for operational metrics, IoT telemetry, and monitoring workloads. The automatic separation between the Memory Store for recent data and the Magnetic Store for historical data delivers strong performance while optimizing storage costs, without requiring manual tuning.

Its SQL interface makes querying time-series data straightforward, and the built-in aggregation and window functions help simplify analytics. The console is also clean and easy to navigate for database management tasks such as retention policies and query execution. Because AWS handles scaling, indexing, storage lifecycle, backups, and ongoing maintenance, teams can spend much less time on infrastructure administration.

While Timestream itself isn’t an AI service, it integrates smoothly with Amazon SageMaker and Amazon Bedrock to support predictive maintenance, anomaly detection, and forecasting solutions based on historical operational data. Review collected by and hosted on G2.com.

Timestream is optimized specifically for time-series workloads, so it’s not a good fit as a general-purpose relational database. Some of the more advanced SQL features you might expect in PostgreSQL or MySQL aren’t available, and organizations that are new to time-series databases may need to rethink and adjust their data-modeling approach. Pricing is also tied to ingestion, storage tiers, and query execution, so for very large telemetry workloads it’s important to keep an eye on costs and monitor usage closely. Review collected by and hosted on G2.com.

Best cloud service provider as it is 100% on-time and less latency Review collected by and hosted on G2.com.

UI is a part which can be improved, if UI is good then it is great! Review collected by and hosted on G2.com.

User friendly interface. Accessibility and readability was prettyeasy. I use it to store data in the data bases Review collected by and hosted on G2.com.

Took a lot of time to load. Initial implementation was difficult for bulk usage. Was hanging a bit Review collected by and hosted on G2.com.

It is simple to use and extremely useful. Amazon Timestream is a kind of temporal database that we use to process data by time interval. It also manages time-consuming tasks such as provisioning some servers and applying and configuring patches. Review collected by and hosted on G2.com.

For tasks that have machine learning and require data to be fed in a temporal manner it works very well. No problem commenting on that. Review collected by and hosted on G2.com.

The features seem like a great product if it actually existed. It was announced at re:invent 2018 but as of June 2020 is still only available in a limited preview. I have made multiple requests for preview access and to get additional information with no responses from the team. Review collected by and hosted on G2.com.

Not only does the product not exist but almost all of these reviews appear to be fake. Look at the review dates. 90% of the reviews were from anonymous sources and all in a 5 day period in April 2019. Review collected by and hosted on G2.com.

AWS Timestream doesn't exist as a generally available product. There's a preview that one can sign up for, but after that, you never hear from the Timestream team. So, it's hard to say what I like about the product. Their web page looks nice, and they did a nice job with the diagrams. So I guess there's that. Review collected by and hosted on G2.com.

Just the fact that I can't actually use the product. Minor detail. Review collected by and hosted on G2.com.

My favorite part of the Amazon Timestream is that it is fast, reliable, fully managed time series database service for many applications. makes it easy to store and analyze trillions of events per day.there are no servers to manage which is amazing! it organizes data by time intervals, reducing the amount of data that needs to be scanned to answer a query. Timestream enables you to easily store and analyze clickstream data at scale to understand the customer journey—the user activity across your applications over a period of time. it automates roll ups, retention, tiering and compression, so time-series data can be efficiently stored and processed. Timestream’s query engine adapts to the location and format of data making it easier and faster to query time-series data. I will continue to use Timestream and spread the word of how efficient it is! Thanks Timestream! Review collected by and hosted on G2.com.

I do not have many things I dislike about it other than there should be a guide or a how to to start the database.It is a overall great service to us for companies or daily life.it is fast easy, simple and overall the best data application I have used in a company. Review collected by and hosted on G2.com.

You don't have to manage a million servers with Timestream because it automatically scales up or down to adjust capacity and performance. This allows you to be able to put your efforts into building your application. I feel what really makes Timestream stand out is that it organizes data by time periods which makes the amount of data need to solve a problem much less. Review collected by and hosted on G2.com.

although this service saves a lot of time it is pretty expensive. Review collected by and hosted on G2.com.

I like the speed of Amazon timestream. It really gives customers the ability to process several events in a short amount of time. Saving time is always valuable in today’s day and age. The quicker we are able to have information transmitted, scanned, and processed to solve issues and daily inquiries is great. Review collected by and hosted on G2.com.

Of course with newer technological advances comes a learning curve. Some of the built in analytical functions are a bit hard for some people to grasp at first. Review collected by and hosted on G2.com.

At my day job, I build a lot of machine learning systems that require data to be fed in a time series manner. Often this means building systems to analyze terabytes of logs [semi]-realtime. All I have to say is - thank god! Like you this will save us a ton of money and should make a lot of the modeling I've worked on a bit easier. Review collected by and hosted on G2.com.

At this point of time it is a bit too expensive. Its value has to be proven to justify its price. Review collected by and hosted on G2.com.