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Tinybird
We help developers who want to build fast APIs faster over streaming data at scale.
Reviews (15)
reviewer2912532
Analytics filters have powered rich URL insights but have also exposed speed and AI limits
Reviewed on Oct 16, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Tinybird is gathering statistics and analytics for the projects. For example, our users enter any specific URL and using Tinybird, we understand their IP addresses, their country, city, device, and we gather this kind of analytics.
I can add that we use filters to understand the period of the URL activity from start to end. We can get analytics for the last 12 months, and its query filters are good and they suit our product.
How has it helped my organization?
Tinybird has impacted my organization positively as we could use a different library, but Tinybird's speed is quite fine, so it helps us to do everything very quickly.
Regarding how the speed has made a difference for my team or business, we compared Tinybird requests with regular SQL requests, and Tinybird is around two times faster.
What is most valuable?
The best feature Tinybird offers is the filter ability with query params.
The query parameter flexibility helps me in my day-to-day work as we use it for simple things such as filtering names, dates, specific countries, and devices. We use the data and convert it to show up in our chart areas, in our pie charts, and in our bar charts, so it is simple to do it with Tinybird.
What needs improvement?
Tinybird can be improved by simplifying it and having more AI features in the future. It can also be much faster because sometimes it can still be a bit laggy.
You can understand it better than me if you start to analyze the things that I mentioned regarding needed improvements.
For how long have I used the solution?
I have been using Tinybird for about one year.
What do I think about the stability of the solution?
Regarding Tinybird's AI capabilities, I think it can sometimes be laggy or sometimes incorrect, but at least it helps to handle a lot of requests, especially if they contain many different filters and parameters.
How was the initial setup?
In my organization, Tinybird is deployed using Vercel.
What other advice do I have?
My advice to others looking into using Tinybird is that if their product contains many specific filters inside and those filters also need some calculations for the database, Tinybird can be a suitable choice.
Regarding Tinybird's AI capabilities, if an AI prompt can make regular query params and send to Tinybird, I do not think there would be any governance issues.
To clarify, Tinybird is deployed on a private cloud in my organization, though I do not exactly know. I would rate Tinybird overall around six or seven because I think it can be faster.
Rose S.
Limited Customization Features
Reviewed on Jan 25, 2024
Review provided by G2
What do you like best about the product?
The platform is not user friendly and intuitive. It lacks to provide performance enabling real time processing and analysis of data. The wide range of connectors and integrations is not impressive making it a breeze to connect with data sources.
What do you dislike about the product?
The limited integrations with platforms hinder the flow of data and collaboration efforts. The lack of scalability and customization options restrict its adaptability to diverse business needs. New users may find it difficult to navigate and fully utilize the features due to the learning curve and complexity of the interface.
What problems is the product solving and how is that benefiting you?
The pricing structure lacks transparency, which is costly, for businesses. Tinybird unable to solve the problems of handling and analyzing datasets in time providing us with instant insights that were previously unattainable. This has decreased my business growth.
Frank B.
Problem of real time data processing
Reviewed on Jan 22, 2024
Review provided by G2
What do you like best about the product?
The platform is less user friendly and not intuitive. It makes analyzing and visualizing data difficult. The performance is not well organized, with slow queries and poor real time updates. The APIs are less flexible not allowing me to integrate with tools.
What do you dislike about the product?
The documentation is not providing instructions and examples. The support team is not always quick to help resolve any issues. Now onto the things I wish need to be improved about Tinybird. While it has benefits, one area that needs improvement is its documentation. It's not as comprehensive as it could be which makes it a bit difficult for new users to navigate and fully utilize.
What problems is the product solving and how is that benefiting you?
The platform's limited integrations make it more difficult to integrate data from sources for analysis. I feel that the user interface needs to be more user friendly as it currently requires some time and effort to navigate and use.
Bhavya J.
Building real-time analytics made simple with Tinybird
Reviewed on Jan 17, 2024
Review provided by G2
What do you like best about the product?
It is easy to integrate with other apps like Confluent Cloud and develop real-time dashboards that provide accurate analytics. It has a simple and easy-to-use interface and turns data into API endpoints, making it easy to scale data warehouses. It is also good for shipping products faster with its CI/CD pipeline implementation. It also offers a powerful testing playground for testing APIs and their functionality.
What do you dislike about the product?
I have been frequently using it for quite some time now and the issue that I faced was with its CLI as it becomes blank and does not show anything, and we have to terminate it and restart the process in some cases.
What problems is the product solving and how is that benefiting you?
It helps in making analytics simple as we have centralized large data sets and multiple teams from different departments use that for their needs to generate analytics. It also makes it easy to scale and provides great performance. Now we do not have to use multiple tools for data analytics and API design, which saves a lot of time and increases productivity to work on real problems.
Maxwel S.
Best tool for building dashboards and develop low latency APIs
Reviewed on Jan 17, 2024
Review provided by G2
What do you like best about the product?
It is simple to use and implementation with kafka and kinesis is also easy. It make deployment easy with its CI/CD pipelines and also provide testing enviroment and make creation of API endpoint quick. It also provide analytics about data and resource usage in its dashboard which helps in making better decisions and has powerful command line interface.
What do you dislike about the product?
Customer support response time was late but they helped in our query. Sometimes importing data from google cloud storage take time other than this I have not faced any issues.
What problems is the product solving and how is that benefiting you?
I majorily use it to design and develop API related to big datas as its data ingestion is really good. It also support SQL and most of our projects support SQL so we don't have to spent our time learning new language which saves us time and increases productivity. Its testing enviroment helps resolving of bugs in API and helps in fixing them in no time to ship them faster.
Pankaj Rao G.
Transforming Data Development with Ease and Efficiency
Reviewed on Jan 16, 2024
Review provided by G2
What do you like best about the product?
Tinybird simplifies development, excelling in real-time analytics with unmatched speed and cost effectiveness. Easy data ingestion, quick querying, and automated API make it a standout choice. Empowering small teams, it's like Clickhouse as a service, accelerating data product development.
What do you dislike about the product?
At first, some things were missing, but they added them fast. Making aggregating merge trees easier to use would be a good idea.
What problems is the product solving and how is that benefiting you?
It helps me explore and make tools quickly. Tinybird works for billing, analytics and finding unusual things. But, it's not so good at handling lots of data fast. This makes our business slower and it's hard to fix big problems.
Monica D.
Deficiency of Customization Features
Reviewed on Jan 04, 2024
Review provided by G2
What do you like best about the product?
There are some problems with clickhouse and materialized views a skilled data engineer handle them. Simplifying the process of aggregating merge trees is not beneficial. Its user interface is bit confusing for beginners.
What do you dislike about the product?
Tinybird is flexible and allows for development of data products it still lacks features due to being a relatively new company. Their Customer Success department is helpful there is room, for development and improvement of the product itself. There are workarounds required to meet needs.
What problems is the product solving and how is that benefiting you?
This lacks to solve the problems of handling and examining volumes of data in time. By Using this progress of my business has decreased.It is unable to resolve issues. There is a steep learning curve.
Andreas T.
I've built 3 products on top of Tinybird
Reviewed on Dec 04, 2023
Review provided by G2
What do you like best about the product?
It's easy to understand, integrate and explore as a developer. Afterwards you don't have to worry about anything, it just works.
What do you dislike about the product?
Some features were not available in the beginning, but they quickly added them.
What problems is the product solving and how is that benefiting you?
We're pushing all sorts of events to tinybird and then figuring out what to do with them later. Since tinybird is so flexible, we can explore and build tooling for new use cases in record time.
Tinybird is currently powering our entire usage-based billing, internal and customer-facing analytics, as well as discovering anomalies.
Tinybird is currently powering our entire usage-based billing, internal and customer-facing analytics, as well as discovering anomalies.
Steven T.
Hands-down the best OLAP database for building real-time analytics products
Reviewed on Nov 08, 2023
Review provided by G2
What do you like best about the product?
Tinybird is incredible for building real-time analytics products. We've tried out various alternatives like Clickhouse Cloud and a custom Redis-based solution, but none of them could match the response latency, pricing, and developer experience that we get from Tinybird.
What do you dislike about the product?
Not much to criticize here – only suggestion I have is for the Tinybird dashboard to incorporate more AI features to help with crafting optimized Clickhouse queries :)
What problems is the product solving and how is that benefiting you?
At Dub.co, we process millions of link redirects weekly and need a powerful OLAP database solution to store and process those clicks and display it to our users (https://dub.co/blog/introducing-new-analytics).
Tinybird is perfect for our use case – not to mention the stellar developer experience and affordable pricing.
Tinybird is perfect for our use case – not to mention the stellar developer experience and affordable pricing.
Thomas R.
An excellent solution for building data products
Reviewed on Mar 27, 2023
Review provided by G2
What do you like best about the product?
Tinybird makes it super easy to get started with data analytics without the hassle. Ingesting is easy, querying is easy, exposing data for your data products is easy. The streaming materialized views concept is fantastic to keep aggregation queries fast and cheap. Tinybird helped us to get started building a complex data product with a very small team. The tinybird team provides excellent support!
What do you dislike about the product?
There are some caveats in clickhouse and materialized views, but nothing an adept data engineer can't handle. Making aggregating merge trees easier to use could be helpful.
What problems is the product solving and how is that benefiting you?
- Building data products fast
- Making big data analytics easy
- Completely managed data infrastructure
- Making big data analytics easy
- Completely managed data infrastructure