TiDB Cloud Reviews

TiDB Cloud is basically used for building scalable, high-availability databases that combine the strengths of OLTP. The main use cases would be for HTAP workloads, STAP workloads, distributed SQL systems, cloud-native databases, or large-scale databases. I have implemented it in making analytics dashboards and e-commerce platforms.

I use TiDB Cloud for analytics dashboards because it supports hybrid transactional and analytical processing. You can query fresh transactional data in real-time without ETL delays. For data ingestion, applications write transaction data into TiDB Cloud. It supports the MySQL protocol, which is easy for integration. It also replicates data to TiFlash for columnar storage with OLTP queries. It has query layers and is useful for visualization tools such as Grafana, which can connect to TiDB Cloud as a data source.

I have also been working on a financial payment system in my personal project. It uses high transactions, ACID consistency, and real-time fraud checks. TiDB Cloud provides strong consistency and high availability. For one of my e-commerce platforms, I used it for inventory tracking and user activity tracking for horizontal scaling. It handles sudden loads well.

TiDB Cloud offers horizontal scalability. You can scale TiDB Cloud simply by adding more nodes with no manual sharding. That is a significant advantage over traditional MySQL setups. It also supports MySQL compatibility, as it supports the MySQL protocol and syntax. It has hybrid transactional and analytical processing for real-time analytics on data, so no separate data warehouse is needed. It supports ACID transactions and high availability.

Another feature of TiDB Cloud is the cloud-native design. It works smoothly with modern infrastructures such as elastic scaling, container-ready orchestration, and microservice architecture. It separates the SQL layer from the storage layer for independent scaling and a flexible architecture. It is an enterprise-grade design.

TiDB Cloud has positively impacted my organization, especially where massive scale and real-time analytics were needed. It powers core cloud services. We have used HTAP workloads, what we call STAP workloads, or the cloud-managed service. My job was to handle the cloud network for financial data.

TiDB Cloud performance can be improved by enabling and tuning TiFlash. For example, use TiFlash replicas for heavy analytic workloads. This will impact query speed for dashboards and aggregation speed. Proper cluster sizing is important, such as adding more TiKV nodes for high throughput. Optimizing SQL and index optimization, such as removing unused indexes, are other ways. Region and data distribution tuning can also help.

Monitoring with Grafana for things such as QPS, latency, and regional hotspots helps catch bottlenecks early, as does monitoring CPU and I/O usage. Utilizing horizontal scaling is also beneficial.

I have been using TiDB Cloud for one to 1.5 years, and I have worked with multiple companies that use TiDB Cloud as their main database. I had quite a good experience with TiDB Cloud and how it works.

TiDB Cloud is considered stable and production-grade when deployed correctly. Most downtime issues come from misconfiguration and under-provisioning, not the core product. It has multi-replica storage using Raft. It separates the SQL layer, so there is no single point of failure. It also has automatic failover. We have seen very few issues. TiDB Cloud is used in FinTech and e-commerce. In terms of stability, it is much better.

Query speed and latency for OLTP is typically a few milliseconds, and it can handle hundreds of thousands of QPS. There is also horizontal scaling efficiency, with no manual sharding required and independence. It provides real-time analytics and data visibility for the organization. Large dataset handling is another benefit. It delivers a certain level of performance for large-scale applications.

I once contacted TiDB Cloud's customer support. Its reputation is considered strong, especially for enterprise and cloud users. My experience varied by support tier. There was 24/7 support available with quick response times and dedicated support engineers. The support was good and strong.

On a scale of one to ten, I would rate the customer support for TiDB Cloud at about a six. It is a good number. You get a fast response with paid plans. This was not the case with the free plans, but the paid plans were much more responsive.

Positive

I basically worked with other solutions before using TiDB Cloud. We used MySQL, but after experiencing TiDB Cloud's automatic sharding, I did not go back to MySQL. TiDB Cloud was giving me the features and performance I needed most. I did not need to look for another one.

I worked with MySQL before choosing TiDB Cloud. It used vertical scaling, so it was a costly and not very cost-friendly solution compared to TiDB Cloud. It was a single node or master-slave setup. It was simple to start with MySQL, and it was a familiar ecosystem. After using TiDB Cloud, I did not switch to anything else because of its compatibility and ease of migration.

In my organization, we reported a strong ROI after adopting TiDB Cloud. The return depends on the workload, scale, and what problems you are replacing. It eliminated manual sharding costs. Before, the team had to maintain complex sharding logic, but after TiDB Cloud, it was a simple architecture with automatic sharding. Infrastructure costs were also reduced. MySQL was replaced with TiDB Cloud plus TiFlash, which leads to fewer ETL costs. It provides better scaling; we avoided vertical scaling, which was expensive. TiDB Cloud allows scaling only when needed.

The pricing for TiDB Cloud depends heavily on how you deploy it. Organizations usually evaluate costs based on scalability needs. The main pricing models are that TiDB Cloud itself is free, and you pay for infrastructure and storage. There was no license fee when we worked with the higher-tier plan. The pricing was almost similar to others, but it provides more functional features. TiDB Cloud is an add-on in terms of functionality. We did not focus much on the pricing, but it does provide more functions and features.

I would rate TiDB Cloud overall at an eight out of ten. It has pretty good horizontal scaling and OLTP use.

TiDB Cloud stands out because it combines traditional SQL reliability with modern distributed scaling. Most systems separate OLTP and OLAP, but TiDB Cloud runs both. It also has MySQL compatibility. There is no manual sharding. Other manual distributed databases sacrifice consistency, but TiDB Cloud provides full ACID, distributed transactions, and Raft replication. That makes it stand out from others.

TiDB Cloud is typically deployed in my organization as a distributed cluster to support high availability. In my company, there was a standard deployment architecture with a service layer behind a load balancer. The second layer was TiKV for distributed storage. TiFlash was optional, but we used it for fast OLAP queries. There were also placement drivers.

TiDB Cloud is a strong, modern distributed SQL database. Its real value appears only at scale, with balanced workloads or on a rapidly growing SaaS platform. It really shines there for high-concurrency and mixed workloads.

I would tell others looking into using TiDB Cloud that it supports horizontal sharding and node replicas. Use TiDB Cloud for write-heavy workloads, as it outshines others for things such as high-concurrency OLTP and high-throughput data. Benchmark real queries and validate the HTAP benefits. This prevents surprises in production. Plan for proper cluster sizing.

We worked mainly with Azure for TiDB Cloud. My overall rating for this product is eight out of ten.

My main use case for TiDB Cloud is like any relational database, where we collect data. There is one project that was rewritten internally, and the whole new flow was built on TiDB, starting from the internal chat to working with record locking. In this system, there are real estate properties that we launch into a process called annotation, where real people reconcile them. There is a target estate and another listing that we found on some platform, and an annotator has to mark it. There is locking based on who opened and got this job, because after that some bonuses to the salary will be accrued and salaries will be recalculated. The entire full cycle is stored in TiDB.

Mostly in our small legacy SaaS solution we still use MongoDB, but I am an advocate of migrating everything possible to TiDB. The latest thing I did was implementing page views on TiDB using a batch that hangs in a cron job and runs via a queue written on Kafka.

My expertise is in widgets, which are small micro frontends to provide our services to clients on their site. These include a lead-magnet widget, a map widget, and an FSBO widget, which is an assistant-manager assistant and a tool for contacting the owner of the property to provide an expert evaluation and offer to become their agent.

To be honest, I have not noticed a big difference with TiDB Cloud compared to PostgreSQL, but the architecture and scalability itself are much more convenient. Nowadays deployment and autosizing for needs and loads are much more convenient. However, for large volumes of data, you have to make archive tables and move annotation records there once a month, for example.

I am not a DevOps expert; DevOps is more involved in the setup. I am more of a client who uses TiDB Cloud as a black box. As far as I know and understand, it can do automatic partitioning of data, which helps a lot for some filters. It can also scale to pods. I did not dig deeply into how exactly we have it deployed and how it is configured, but I know about its capabilities.

I do not really know about any other features of TiDB Cloud because I do not use anything else from relational databases right now. What was new and fresh for me is that I liked working with the JSON column type and with built-in functions; it is very convenient. It used to be much more problematic.

Speaking of the features I use as a developer, I find searching for elements in JSON objects particularly convenient in TiDB Cloud. That is what is really convenient. Everything else is in automatic mode.

It is very unusual and jarring that the IDs in different tables jump and do not start from zero.

I have been using TiDB Cloud for the last four years.

I have experienced full 100% stability with TiDB Cloud. However, sometimes there were issues precisely before we implemented archiving of large data. Then occasionally there were slowdowns. Archiving now runs once a month, and everything works more or less stably.

There are only critical situations when asynchronous tasks for data synchronization are launched because many different independent teams work, and sometimes they can create an unpredictably large load.

TiDB Cloud is deployed in our organization in a public cloud, not locally. I did not check if there is a TiDB image in Docker, but I am almost sure there should be one. We use it on dev environments and in production in Kubernetes. As for more specifics, I cannot say anything; I do not know about access and how it is deployed. It is hosted inside Kubernetes.

I would rate the quality of TiDB Cloud's customer support as unknown because I have not contacted them, and those questions are more for DevOps.

We used MongoDB, MariaDB, PostgreSQL, and a long time ago MySQL. We also used Oracle on one of the products. There were probably the most questions with Oracle because support is very complex and everything is very dependent on versions. Now, as far as I know, TiDB is constantly updated and maintained, and basically there have been no problems. It looks seamless and is a one-button click.

Compared to MongoDB, there is basically no choice; you have to move away from MongoDB because the runtime behavior of the code in production and in development is very unexpected. The data volumes are huge, with collections of 12 million records and so on. Because you work with them in an unstructured way, their volume and the objects themselves changed, their type changed, and maintaining old records becomes impossible. This now causes a problem when moving to a relational database. If we had been on one from the beginning, there would be fewer problems. The main complaint about MongoDB is that it deserializes objects if it does not find the required indexes and just starts killing the server by memory.

The general point is increased fault tolerance of the system.

There is a separate department in the company that handles pricing, implementation cost, and licensing for TiDB Cloud. A regular developer does not deal with it, and the decision was not made by me. TiDB was approved as an internal standard before I joined the company.

I am satisfied with this aspect, as far as I know and use it.

I do not know how TiDB is with vector tables, but I know they are somewhat in vogue right now thanks to the AI boom. However, the boom seems to be gradually fading, and vector tables may not be needed.

I do not know the competitors or who is a competitor to TiDB Cloud, because all other databases are hard to host yourself. I do not have specific advice for specialists who are considering using TiDB Cloud.

The reason I choose a rating of nine is that there is always room to grow; you cannot overpraise. This is quite a high score in my opinion because I have not encountered any task that could not be solved in TiDB. Unfortunately, I do not have experience comparing it with competitors, but as far as I know, there are no impossible tasks.

As far as I know, our TiDB integrates automatically only with Big Data or BigCloud, though I do not remember exactly what the tool is called that business analysts work in. All these tasks, as far as I remember, are integrated manually. It would probably be beneficial to have a UI where the entire data synchronization process can be automated.

I rate this product a nine out of ten.

My main use case for TiDB Cloud is that I have used it for testing the vector search for my internal testing purposes, and I have also checked the high availability and auto scale features in TiDB Cloud.

In my internal testing, I have a scenario where I need to build a small application with vector search, and for that, I have deployed TiDB in the cloud using the vector search feature by feeding some text or content and training the model to fetch data with that vector search index.

Regarding my main use case, I find that although it is somewhat costly, TiDB Cloud is best for high availability use cases because we do not need to add the number of PD nodes or TiFlash nodes; it scales up according to our workload, and we do not need to worry about server crashes or resource over-utilization problems as it automatically scales up and down based on our workloads.

TiDB Cloud is best for high availability use cases, and we can also explore more AI features including vector search.

I would like to add that we can enhance security using TiDB Cloud with private and public endpoints, ensuring that our data remains secure, especially for high-security use cases involving very confidential data, making this feature one of the best.

TiDB Cloud has positively impacted my organization because using the vector search feature has made me explore more about it in TiDB, and I have tried to implement that in our organization, and I am currently working on it.

I have explored a feature such as text-to-query, which allows us to avoid writing raw queries; we can just input our own sentence, and the text-to-query feature converts the text into a query which can then be used in the database.

While TiDB Cloud is good for high availability, I think there are some bugs when using the TiFlash feature, sometimes in the TiKV component as well. In TiFlash, I have discovered that it is not suitable for high concurrency since increasing the query concurrency causes TiFlash to overload, sometimes resulting in query failures, while TiKV handles concurrency better but is more focused on row-based data for smaller amounts of data. It would be great if these issues in TiFlash with high concurrency are effectively managed.

According to user experience, I find TiDB Cloud to be more useful for bigger queries, but I also notice complications occurring at times.

When going through the logs, I sometimes find that there are no details regarding errors. I have noticed that while the TiDB documentation lists some error codes to troubleshoot issues, it lacks workarounds or solutions for those error codes, making it not very customer-friendly. I experienced this when I faced an error and could find the error code but not the solution.

I have been using TiDB Cloud for more than one year.

TiDB Cloud is stable based on our deployments. If it is deployed in a cross-region or uses placement rules, it remains stable due to data storage in multiple availability zones.

The scalability of TiDB Cloud is automatically configured, allowing it to scale out when workloads increase and automatically scale in when workloads decrease, which means we do not need to worry.

When discussing customer support, I find that the TiDB community is very active compared to other databases. They quickly respond to questions or feature requests, and when I submitted bug reports, the community provided solutions within three business days, which I appreciate.

Previously, I have used self-deployed TiDB, but I find TiDB Cloud to be better than the self-deployed clusters.

I previously explored TiDB in self-deployment, which led me to evaluate TiDB Cloud as well before starting with it.

I see a return on investment with TiDB Cloud as we reduce the time spent on maintaining and monitoring since everything is automated, including the auto-scaling feature when large workloads arise. Monitoring is deployed automatically, relieving us from manual monitoring responsibilities, which is a significant part concerning ROI.

I would rate TiDB Cloud 10 out of 8; the two points I reduced are due to cost concerns and issues related to user-friendliness.

I take off those two points mainly because of the cost and the user-friendliness issues experienced.

My advice to others considering TiDB Cloud is to keep the cost in mind. If cost is not a concern, I believe TiDB Cloud is the best option among traditional databases due to its distributed architecture which supports high availability and auto-scaling. I also think the TiFlash engine is a good choice for analytical data loads, so I strongly suggest going with TiDB Cloud.

The only additional thought I have is regarding the cost since many customers are worried about it.

I think the questions asked for the reviews are good, but it would help if you waited longer for answers, as sometimes you move to the next question too quickly.

My overall rating for TiDB Cloud is 8 out of 10.

Our main use cases for TiDB Cloud are handling large-scale transactional data and running real-time analytics on the same platform for scalable applications.

In one project, I used TiDB Cloud to support a GenAI RAG pipeline where we processed documentation, generated embeddings, and served responses. I helped monitor cloud workflows, managing deployment, configuring, and tracking pipeline performance to ensure stable response times and reliable processing.

The best features of TiDB Cloud are its horizontal scalability, MySQL compatibility, high availability, and real-time HTAP support. I also appreciate that it can handle both transactional and analytical workloads in a single platform, which reduces infrastructure complexity and improves performance for data-intensive applications.

TiDB Cloud's managed cloud infrastructure has reduced maintenance for our team and allowed us to focus more on development and analytics instead of database operations.

TiDB Cloud has scaled horizontally very smoothly in our experience, meaning we can add more nodes during traffic or data growth.

TiDB Cloud has positively impacted our organization by improving scalability, reducing database maintenance effort, and enabling real-time data processing for faster decision-making. It also simplified our architecture by combining transactional and analytical workloads in one system, which improved our efficiency and reduced operational overhead.

Using TiDB Cloud improved query performance by roughly thirty to forty percent for real-time dashboards and reduced database maintenance and scaling efforts significantly.

One area where TiDB Cloud can be improved is making advanced monitoring and query optimization insights more intuitive for new users because understanding distributed query performance still requires a learning curve.

Another improvement I would suggest for TiDB Cloud is enhancing the built-in migration tooling, especially for complex legacy databases, so onboarding and data migration become even smoother with less manual tuning required.

The main areas for improvement are advanced observability, debugging experience, and more AI-focused tooling.

TiDB Cloud would benefit from better real-time query debugging tools that can clearly explain why a distributed query is slow and suggest optimizations automatically.

I have been using TiDB Cloud for around two years in data-intensive and scalable application projects.

TiDB Cloud has been very stable in our experience regarding scalability. We did not face any major downtime in production.

The biggest difference for our team has been the horizontal scalability in TiDB Cloud because it allowed us to handle increasing data volume and traffic without downtime or complex database sharding, which made scaling much easier and more efficient.

TiDB Cloud has scaled horizontally very smoothly in our experience, meaning we can add more nodes during traffic or data growth.

Customer support for TiDB Cloud has been good in our experience. We usually get timely responses through their support tickets, and for critical issues, the response time is quite fast, especially with their paid support plan.

Before using TiDB Cloud, we were using a traditional MySQL-based setup with manual sharding. We switched because scaling was becoming complex and time-consuming.

We procured TiDB Cloud through the AWS Marketplace, which made onboarding and billing integration with our existing AWS setup much easier.

TiDB Cloud's pricing is generally flexible and usage-based, which works well for us because we could scale costs with workload. Setup cost was low since it is a managed service, and we did not need heavy infrastructure setup or maintenance.

Before selecting TiDB Cloud, we evaluated a few other options including Amazon Aurora, Google Cloud Spanner, and a self-managed MySQL or PostgreSQL setup.

I would advise clearly evaluating your workload needs first, especially if you are dealing with high-scale transactional data or need real-time analytics, because TiDB Cloud performs best in those scenarios.

TiDB Cloud is a strong choice if someone needs scalability and real-time data handling without managing complex database infrastructure. I give this product a rating of eight out of ten.

My main use case for TiDB Cloud is to explore and learn about the product, since it is an open-source database. I wanted to understand how it works so I could illustrate and communicate about it effectively.

The primary goal has been learning about TiDB Cloud so I could speak knowledgeably about it.

In my opinion, the best features that TiDB Cloud offers are horizontal scaling, high availability for platforms, and its open-source nature, which looks familiar to engineers since it resembles MySQL.

Horizontal scaling is valuable to me because databases that scale vertically hit a limit, and something that can automatically deploy another node to horizontally scale and do it automatically is of immense value to anyone running a SQL-based database. Regarding the open-source aspect, the biggest benefit is that there is no vendor lock-in, so I can use it for different services and integrate it with various products and solutions without being locked into AWS and subject to their terms and conditions. This allows me to create my own value and my own path.

TiDB Cloud has impacted my organization positively by being a good partner. I have met many talented people there, and it was an introduction to the space for me.

I think TiDB Cloud could be improved from a marketing perspective, as it competes with PostgreSQL in the space, where many people know or use PostgreSQL. The question is how they position themselves to be in the same aspect as PostgreSQL, because I feel that is one of their biggest barriers.

From a technical perspective, the main improvement I see is not necessarily being designed with the implication of being compatible with PostgreSQL, but I see an opportunity where they could create something that can re-architecture without being related to PostgreSQL. I also think it should be able to do all of that without downtime, but I have heard that is not currently the case.

I have been using TiDB Cloud for about six months.

TiDB Cloud is stable.

TiDB Cloud's scalability is the best in the business.

I do not really need customer support because I am only using it in a private capacity.

I would advise others looking into using TiDB Cloud to conduct a deep dive on a white paper and learn all the intricacies of your database. It makes sense to take a meeting to learn about it specifically for your environment, or do what I do and experiment with it in a test environment and then advance into a very informed meeting.

The biggest thing about using TiDB Cloud depends on the context. I am discussing using it in a smaller instance, but if I consider some of the results they produced for databreaks or last scene, those are the significant opportunities down the line. I think those are the things I would highlight and show to illustrate what someone would look for.

Since TiDB Cloud is open source and we are using the open-source free version, we have not adopted anything from a paid perspective, and I do not have that need for it yet.

I would rate this product an 8 out of 10.

As a native TiDB user, I install TiDB on EC2 machines, but I wanted to see how TiDB Cloud helps in seamless integration with that ecosystem, so I conducted an experiment with TiDB with Vector and other features.

I have a use case where I wanted to try Vector Search, so I thought of using TiDB Cloud, and I conducted experiments and figured out the use cases for that.

The best features TiDB Cloud offers are mainly because of the easy scale-up of compute and data nodes. On an on-premises cluster that I manage, I would have to procure a new machine and add that to TiKV, but instead, I can easily manage the TiDB nodes, which is the main advantage that I see with it.

In an existing cluster that I manage on-premises, I have to get a new machine, do patching, and make the user SSH, but with TiDB Cloud, I can simply click and scale independently, which is the main advantage that I see with it.

The main advantage that I see with TiDB Cloud is the easy scale-up and scale-in without the need to buy any machines or do patching. It is less hassle; it used to take at least a couple of hours to bring in a new node, patching, and all those other tasks, but with TiDB Cloud, it takes very few minutes, probably a couple of minutes to bring up a new node.

Definitely, the employee and the team will be saved because they do not need a DBA to exclusively set the servers, patching, and all those other tasks, but for money saved, I am not sure about this point since I have not had a real adoption of that.

I think my use case has a direct migration DM tool, which brings the data from MySQL to TiDB layer, and I am not sure if that is available on TiDB Cloud, so that is one thing I might not be aware of, or else that feature may not be present in TiDB Cloud.

One thing I want for TiDB Cloud is the DM because I specifically pull the data from MySQL and put it on TiDB, but with TiDB Cloud, I do not think that DM is available.

Having said that, the one feature that I am exclusively using is the direct migration from MySQL to TiDB, which is a continuous replication from MySQL to TiDB, and I think it lacks in TiDB Cloud.

If you do not have an option to have a replication from MySQL to TiDB, you can go ahead and simply use TiDB Cloud because it is far more efficient than maintaining TiDB on-premises, but if you have a DM kind of solution, which is not yet there in TiDB Cloud, you might have to stick around with native TiDB.

I have been using TiDB Cloud for six or seven months.

TiDB Cloud is stable in my experience.

Scalability is very positive for TiDB Cloud, as DBAs can easily add a node if they figure out the nodes are not sufficient to handle the traffic, so I can give scalability a rating of ten out of ten.

I have not interacted with customer support for TiDB Cloud yet, as I conducted some experiments and have not fully moved to production, hence I have not tested the customer support.

The initial setup with TiDB Cloud is straightforward; the manuals, documentation, and everything were much simpler and easier to execute, so I have not had a hard time doing that.

Performance-wise, I do not see a problem with TiDB Cloud because I already use TiDB on-premises, which is pretty much similar to TiDB Cloud, so I am not seeing much of a difference.

I am partners with PingCAP.

Since I found that the DM is not there, I have not gone beyond the pricing point.

I heard about the pricing because I conducted only an experiment; since I found that the DM is not there, I have not gone beyond the pricing point.

Everything is simpler to adapt in TiDB Cloud versus a normal TiDB, apart from that, I do not wish for anything else to be easier or more flexible. I would rate this review an eight out of ten.

My main use case for TiDB Cloud is developing technical documentation related to vehicle services, such as buses and trucks for Iveco.

TiDB Cloud helps with that process as it is a Content Management System, which allows me to organize all the information in a chaptering structure. I start from the Bill of Materials of the vehicle and use drawings released by engineering to develop technical documentation for owner manuals, service manuals, and similar materials.

TiDB Cloud has positively impacted my organization by improving documentation management. It is better than the previous system where documents were developed using Word or Interleaf, as using TiDB Cloud allows us to have everything stored in a good archive that we can read and use for new projects.

The improved archive and accessibility help my team by saving time, mostly because we can find information more easily than before.

The best features TiDB Cloud offers are the possibility to easily reuse information in different documents, which really stands out to me.

The ability to reuse information across documents helps my team as it saves time and reduces errors because we do not have to rewrite the same information anymore.

TiDB Cloud has positively impacted my organization by improving documentation management. It is better than the previous system where documents were developed using Word or Interleaf, as using TiDB Cloud allows us to have everything stored in a good archive that we can read and use for new projects.

The improved archive and accessibility help my team by saving time, mostly because we can find information more easily than before.

TiDB Cloud can be improved, particularly because the interface is very old. I think it would be helpful to have a new interface.

I have been using TiDB Cloud for ten years.

TiDB Cloud is stable.

TiDB Cloud's scalability is good as it can handle growth easily.

Customer support for TiDB Cloud is quite good based on my experiences. I would rate the customer support a ten.

Positive

Before TiDB Cloud, the company decided to switch from a different solution.

I have not seen a return on investment from TiDB Cloud.

I do not have experience with pricing, setup cost, and licensing for TiDB Cloud because it is managed by the IT team.

I did not evaluate other options before choosing TiDB Cloud.

I use TiDB Cloud for my PAT environment to test some features in TiDB.

I have used TiDB Cloud to test TiFlash and TiKV performance and compare that with PostgreSQL, which I am currently working with.

I explored features such as analytical query performance with TiDB Cloud, where I examined the options in distributed systems and how a distributed database can help with data processing and other tasks.

According to my experience, TiDB Cloud is very easy to use because we don't need to maintain much in TiDB. All the activities are mostly automated there, and we can easily monitor the performance. We don't need to manually check the health checks and other statistics.

The automation in TiDB Cloud helps my daily workflow as it can generate automatic charts according to our workloads, and we can analyze the queries easily using this monitoring feature. Unlike traditional databases, we don't need to monitor the performance and other statistics manually. Instead, in TiDB Cloud we can use the features it comes with.

I think TiDB Cloud is very useful for beginners because of one feature I have noticed: Text to SQL. This feature means we don't need to write exact queries.

The distributed database options in TiDB Cloud have helped me because we can place the data in multiple data centers and multiple nodes. Due to this, when we are accessing some data, it won't affect all the nodes. It will only focus on the node where the data is present, and other users can still use the other data centers to fetch the data effectively.

From my point of view, TiDB Cloud requires more nodes to run the environment because for a self-hosted environment it needs to deploy three PD, three TiKV, and two TiFlash minimum. I think this is more costly than our traditional databases such as MySQL, MongoDB, or PostgreSQL.

We can improve the performance of TiDB Cloud for customers by reducing the cost and enhancing features such as processing large data by using minimal resources.

The main concern for my score of eight out of ten is about the cost. Additionally, due to its cluster and distributed architecture, it is not beginner-friendly for freshers and starting customers.

As I already mentioned, the cost is the main concern in TiDB Cloud, and also its architecture needs to be made more user-friendly for beginners.

I have been working with TiDB Cloud for more than one year.

The most important advice I will give to others looking into using TiDB Cloud is that cluster-level knowledge such as distributed systems is necessary. We need to understand the architecture and the flow of data and other details about the cloud. Additionally, we need to know about analytical and transactional workloads, which is the most important thing about TiDB Cloud database because it is designed for that. My review rating for TiDB Cloud is eight out of ten.

We use an open-source tool called Prometheus. It is an available offering with extensive documentation. The primary purpose of using a time series database like Prometheus is to collect metrics of various activities. These activities can be on the user side, infrastructure side, or behind the scenes where the software is running.

There is a wide variety of use cases for time series databases, mainly focused on collecting and analyzing metrics. For example, you might want to track how many active users log into your product over different periods—minutes, hours, days, weeks, or months. This data can help you understand user behavior and activity trends.

Time series databases record data points over time, allowing you to recall past data or visualize current activity. This is useful for monitoring user engagement, understanding the geographic distribution of your user base, and many other metrics.

We use Prometheus for collecting metrics and Grafana for visualizing them. Grafana allows us to create real-time charts and graphs that display how data changes over time. For example, if you are running an e-commerce site, you might see increased user activity in the evenings when people are more likely to shop.

By combining Prometheus with Grafana, we can track events such as payment initiations on an e-commerce site. Prometheus records the events, and Grafana visualizes them, showing trends and spikes in user activity

Understanding the use of a product and its impact across various areas is essential. For example, if you want to analyze a downward trend in sales, TiDB Cloud can help identify the factors affecting user behavior. It provides valuable insights into what is going on and why. While it can be a broad topic with many technical details, TiDB Cloud offers a comprehensive solution to understand these metrics and trends effectively.

TiDB Cloud has a broader scope that offers multiple services. It can be compared to major cloud providers like AWS, Microsoft Azure, and GCP. Just as these providers offer various services under the umbrella of their cloud platforms, TiDB Cloud also has multiple offerings. For instance, it includes tools like Prometheus and Grafana. TiDB Cloud can be seen as a domain that encompasses various tools and services, making it similar to how AWS, GCP, and Azure operate in the cloud space. These tools are widely recognized and commonly used for managing and tracking data events over time.

If you are using a product managed by a cloud provider, such as AWS or Google Cloud, you benefit from various management tools. For instance, AWS offers CloudWatch for tracking metrics, while Google Cloud provides Time Series Insights. These tools are managed by the cloud providers. As an end user, you primarily need to pay for the service, and the cloud provider handles most of the management tasks.

If you choose to use open-source tools like Prometheus, you will need to manage them yourself. It's a trade-off between convenience and cost. Opting for a managed service means you pay more but have less management overhead. On the other hand, using open-source solutions can reduce costs but requires you to handle the entire management of the infrastructure and database, such as ensuring uptime and provisioning resources. TiDB Cloud offers a reliable, managed solution that ensures availability and performance without the hassle of self-management.

I never really had an issue since we managed the database ourselves. We had many alerts, monitoring systems, and processes to handle everything, including deeper analytics. Many key editing tasks were challenging, but as you progress, you understand at what stage to handle them so things work properly. However, if you're working on a much larger scale and managing the infrastructure of a time series database, it becomes difficult. 

Technical support for TiDB Cloud is actually quite good. Since it is an open-source tool, we have extensive documentation available on the internet and a supportive community you can reach out to. If you choose a cloud-hosted provider, they have a tech team and a support team that responds quickly and manages any issues that arise while you're working. As an open-source tool, TiDB Cloud has comprehensive documentation with answers to almost everything.

If it's self-hosted, the initial setup can indeed be a complex challenge. As you continue to maintain it, managing it becomes slightly easier. On the other hand, using a cloud provider might offer additional benefits compared to using an on-premise solution

There are a few pitfalls and some complexity, but overall it's highly recommended. It's particularly useful for tracing the applications and use cases of complex data.

I recommend the solution. The advice is to use TiDB Cloud for any product or evaluate it based on your use cases. Consider what is important for you: whether you can manage it yourself or prefer to delegate those efforts to your provider, who will handle things for you. TiDB Cloud is powerful for connecting your metrics to understand behavior, both on the product side and the insight engineering side. Additionally, TiDB Cloud is useful for identifying issues if something goes wrong.

Overall, I rate the solution a nine out of ten.

In production, we use the cloud, but in other environments like development and integration, we use self-managed. We store quite a lot of data on TiDB Cloud because it is a scalable database that supports tons of data with online and offline analysis, and online transactions.

Our company focuses on transportation support, with many sensors installed on cars and trucks that collect a lot of data about them. Truck owners can then use this data to analyze their cars and their business to support and grow their business.

I would like to share how we calculate the speed of the car and the value of the truck, as all the CRUD operations about the data happen in TiDB Cloud.

In my experience, the best feature TiDB Cloud offers is that whenever we want to scale up or scale out our database, it is very simple—just a simple click, and it will scale out automatically.

I appreciate the speed of the scaling feature because it is very fast, and the lack of downtime is also my favorite aspect.

There are cost savings because of TiDB Cloud.

I would like to share some specific details on the cost savings: first, we save a lot of money on hardware, second, we have fewer employees needed for maintenance, and third, we have less downtime which helps our business be much more successful. These are all advantages that TiDB Cloud provides.

I have not really noticed any areas where TiDB Cloud could be improved or faced any challenges.

I have not used TiDB Cloud at all, but I have been using TiDB, the self-managed cluster for about half a year.

I do not know much about the technical details of TiDB Cloud, so I cannot answer questions about how we process or analyze that sensor data, including if we run real-time queries or batch jobs.

The performance of TiDB Cloud is very good under heavy workloads and spikes in traffic; it handles the traffic very well, and we have never encountered any downtime because of peak traffic.

TiDB Cloud is a very good choice when you are handling a massive set of data and also want high performance, easy scaling, and high availability.

It is not easy for our team to adopt TiDB Cloud because it is quite complicated. Even though you have provided very detailed documentation, it still takes us a lot of time to work through the whole document to establish best practices on TiDB Cloud.