We use Amazon Timestream as a data historian for IT data. It stores all individual measurements of our customers' IoT devices for a certain period of time, allowing them to perform time-series-based analyses on top of it.
Amazon Timestream is a fully managed, maintenance-free database offering real-time data handling and seamless long-term data aggregation without merge operations, enhancing scalability and speed for IT environments and IoT data.


| Product | Mindshare (%) |
|---|---|
| Amazon Timestream | 4.8% |
| Microsoft Azure Cosmos DB | 14.9% |
| MongoDB Atlas | 14.2% |
| Other | 66.1% |
This service is customizable and user-friendly, making it a preferred choice for managing time-series data efficiently. Users find it beneficial for real-time analytics, monitoring application health, and automating data pipelines. While data charge management and schema design require attention, active collaboration with AWS is ongoing for feature improvements. Increasing batch size for indexing and simplifying the interface are areas identified for enhancement. The database's scalability is highly appreciated, allowing easy management of data collection and storage.
What are the key features of Amazon Timestream?Industries use Amazon Timestream to manage real-time analytics and application health monitoring. It tracks customer data size, automates pipelines, and supports time-series analyses for scaling. Organizations employ it for telemetry data management, queried in projects like microgrid solar energy, acting as a data historian for storing IoT device measurements.
| Author info | Rating | Review Summary |
|---|---|---|
| VP Global IoT Solutions at 1NCE | 5.0 | We use Amazon Timestream as a data historian for IT data, allowing time-series analyses of IoT devices. It's the only suitable time series database from AWS, though we are actively discussing additional features with their engineering teams. |
| Data Engineer at Tiger Analytics | 4.5 | In my company, we use Amazon Timestream for storing real-time telemetry data in a time series database. It's valuable because updates are automatic without needing merges. However, improvements are needed since data can't be deleted manually, only through retention profiles. |
| Software Engineer at Zyrone Energy | 4.5 | I use Amazon Timestream for a microgrid solar project and appreciate its ease in collecting and storing data, as well as its scalability. However, it could be more user-friendly for beginners, especially in understanding queries and integration with other AWS services. |
| Software Engineer at Indexnine Technologies | 4.0 | I use Amazon Timestream to analyze and aggregate data based on time functions. It's valuable for quickly aggregating a decade's data, but I need to manage it carefully due to costs and challenges in arranging the database schema. |
| Principal Software Engineer at Securonix | 4.5 | I use Amazon Timestream for real-time analytics and monitoring application health. It's maintenance-free, customizable, and real-time with no lag. I'd like larger batch sizes for faster indexing. I chose it over InfluxDB to lower maintenance costs without additional infrastructure. |
We use Amazon Timestream as a data historian for IT data. It stores all individual measurements of our customers' IoT devices for a certain period of time, allowing them to perform time-series-based analyses on top of it.
Using Amazon Timestream has been seamless due to its integration within the AWS ecosystem and ease of use for the engineering team.
Amazon Timestream is the right database for our job from AWS. It is the only time series database they have, so there are not many options.
We are working on a few open change requests with the engineering teams on AWS's side. There are certain features that we would like to see added and we are collaborating with the product teams on these areas.
We added Amazon Timestream to our portfolio in early 2022. We reintroduced it with our data historian around that time for storing and analyzing IoT device data.
Although there have been outages here and there, these are usually ones that are covered in the media and affect everyone globally. AWS addresses security bugs and other issues very timely and responsively.
Amazon Timestream is a serverless service, so scaling is not something we actively manage. It just scales automatically as needed.
Amazon has one of the best support teams in the industry. We have been on enterprise support since we founded our company back in 2018, and it has been, by far, the best support we have encountered.
Positive
The initial setup was straightforward as it integrated well within our existing AWS ecosystem and tooling support.
I would absolutely recommend Amazon Timestream to others. I'd rate the solution ten out of ten.

In my company, we have data that needs to be stored, at least in some kind of time series database. We used to get the telemetry data from the devices in real-time, so we have to store them with Amazon Timestream whenever the data is coming in the stream in real-time.
I would say that considering the version that the tool provides, we don't have to do any kind of merge operation or any other update. If some different value comes, like if you want a data value, we can keep the key dimension value the same. It will update the rest of the values, measurement values, and all, so this is why we don't have to do anything extra to merge the tool and all the updates.
There are disadvantages when it comes to time series databases since you can't delete anything from Amazon Timestream data. You can just have the retention profiles on it, after which it will delete itself, but you can't forcefully delete it, making it an area where improvements are required.
I have been using Amazon Timestream for six months. My company has a partnership with Amazon.
It is an easily scalable solution. When it comes to the retention period, if someone wants to change, they have to define it at the start. Later on, if users want to change it again, like, or increase the retention policy, then they have to create the table again and do so, and if it is not done, then we face problems. It will increase the retention, but when you try to insert a record or an older record that is not included in the range of your retention period, then you can face some problems and, like, it will throw some errors. The tool is scalable, but it should be defined at the start as to how much retention you want.
For scalability, I rate the tool a six or seven out of ten.
If you drop a message, the solution's technical support will definitely reply. My company only uses support for some use cases, but not most of the time.
When it comes to the product's deployment phase, everything is managed by AWS, so it is a managed service. If someone doesn't know about the time series database, they might face some difficulties or some challenges. If a person keeps on working on the tool, then such a person will find out how the product works and can work on it.
The tool is not really easy to use. If someone wants to use the tool, they can research and use it, and it won't take much long.
I don't think my company maintains the tool.
I can recommend the tool to others based on their use cases. If someone has a use case where they have some kind of Amazon Timestream data coming in, they can definitely use it, but they have to be cautious about some update and deletion parts. People need to think before using the tool.
I rate the tool an eight and a half out of ten.

I use Amazon Timestream for a microgrid solar project at my company, writing queries for things like state of safety and state of charge.
What I like best is that the tool is easy to collect and store data and is fast and scalable. The fully managed database is easy to understand.
The solution could be improved by making it easier for new graduates like me to use. Better explanations of queries and how to use them with other AWS services would help.
Sometimes, I have issues with complicated queries and errors, but I use resources like ChatGPT and get help from colleagues to solve problems.
I have been working with the product for three to four months.
I rate the tool's stability an eight out of ten.
The tool is scalable, but I've had some challenges with time series data. For scalability, I'd give it a seven point five out of ten.
Amazon Timestream's pricing seems manageable to me.
Overall, I'd rate Amazon Timestream nine out of ten. I would recommend it to others, especially students and recent graduates working on data analytics and real-world business cases. It's very useful for learning about database queries.

I use the solution to analyze and aggregate data based on the time functions.
We are currently having an issue with data management. You can quickly aggregate data from the last ten years with Amazon Timestream.
You have to manage the solution carefully because it charges you based on the amount of data you send from the database. Arranging the database schema is a bit challenging. When you design the schema, you need to be careful how much data you want to store and how much data you are going to retrieve.
I have been using Amazon Timestream for one year.
Amazon Timestream is a stable solution.
The solution’s initial setup is really easy.
Amazon Timestream charges based on the amount of data you can convert to a database. For 1GB of data, the solution charges $ 0.01 in the US region.
I would recommend Amazon Timestream to people with a lot of continuously incoming time-relevant data. It is really easy for a beginner to learn to use Amazon Timestream for the first time.
Overall, I rate the solution an eight out of ten.

We use the solution for real-time analytics and monitoring our application's health. We track things like customer data size and use it for data pipelining. We automate our pipelines, store data, and perform analyses to manage scaling.
The best things about Amazon Timestream are it's maintenance-free, customizable, and has no lag issues. It's always real-time.
The tool could be improved by increasing the batch size from one hundred records to five hundred or a thousand to speed up indexing.
I have been using the product for three years.
Amazon Timestream is a stable product, and we haven't encountered any issues.
Our company has 500-600 members, with over 100 in development, and many use TimeStream across different services.
We talked to Amazon support about three years ago when evaluating the tool against InfluxDB to help production things.
Neutral
The tool's deployment is straightforward.
We don't see high costs with Amazon Timestream, which may vary by company.
We chose the tool over other products like InfluxDB to reduce maintenance costs and avoid needing separate infrastructure.
We use the tool with AI for customer data analysis as part of our internal product. It's a medium effort for beginners to learn; it's not too easy but not too hard. Overall, I'd rate Amazon Timestream eight point five to nine out of ten based on my experience. Integrating it wasn't difficult, and we didn't face any challenges. My advice for new users is to choose the right dimension names for better query performance and structure their data correctly before indexing.