Tiger Cloud - Annual Commit
TigerDataReviews from AWS customer
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Effective tool for data insights
What do you like best about the product?
It is easy to access, analyze and visualize data. I really liked how it processes large datasets and provides clear, actionable insights to look for. The dashboard for pc version is also user friendly and customizable, and helps to stay updated for the changing trends in the market. It has definitely improved the speed and accuracy of decision-making in my work. Also, i preferred it's former name (timescale) but new name is also good.
What do you dislike about the product?
there are times when the interface feels a bit heavy, especially when dealing with large volumes of data. The mobile version could also be more optimized for smoother usage on the go with better UI.
What problems is the product solving and how is that benefiting you?
Currently, I am catering a client where i have to deal and analyze good size data where tigerdata comes into the picture.
My Experience using tiger data
What do you like best about the product?
I like the clean and intuitive UI the most. It’s easy to navigate, and I appreciate the ability to pause services whenever needed. The availability of connectors, especially for Amazon S3 and Kafka, makes integration smooth and very useful.
What do you dislike about the product?
The pricing feels a bit high and could be more flexible, especially for smaller projects or startups.
What problems is the product solving and how is that benefiting you?
TigerData solves the usual trade-offs between real-time and analytical workloads: I get fast queries on fresh and historical data both, without needing to build and maintain complex pipelines. Its compression and tiered storage help keep costs down even as data volume grows. Also, the native integrations (lakehouse / S3) reduce overhead, making it easier to focus on insights rather than infrastructure.
Efficient and powerful database platform for scalable analytics
What do you like best about the product?
TigerData stands out for its extremely fast setup, reliable ingestion speeds, and intuitive cloud interface, making it easy to start and scale even complex analytical workloads. Its full PostgreSQL compatibility—plus handy vector database tools—enables seamless migrations and flexible querying without the need to learn new languages or disrupt existing workflows. Active community support through Discord and Slack, plus robust documentation, mean help is always available for developers and admins. Features like continuous aggregation, compression, and automatic partitioning allow teams to optimize performance and save on cloud costs, while its metrics dashboard provides clear insights into database health and usage.
What do you dislike about the product?
Although TigerData is highly performant, the UI can become slow to load when managing many tables, which impacts workflow efficiency for larger projects. Some users note the absence of advanced visualizers for vector data—features seen in competing products—which can limit analytic visualization capabilities. On rare occasions, initial self-hosted deployments may require extra troubleshooting, but most issues are quickly addressed by updates or community help. Additionally, TigerData’s licensing and query costs can be higher compared to certain open-source or basic database offerings, so budgeting is important when scaling up.
What problems is the product solving and how is that benefiting you?
TigerData enables reliable and high-speed storage and analysis for massive time series data, solving scaling bottlenecks and ingestion speed limitations experienced with traditional databases. It helps the team efficiently run real-time analytics, minimizes downtime, and saves on cloud costs thanks to automated compression and partitioning features. This has improved decision-making speed and operational reliability for data-driven products.
Efficient easy to use platform
What do you like best about the product?
The platform provides various easy-to-use tools for analytics, making analytics simplier
What do you dislike about the product?
Need some time to learn features, have slow customer support.
What problems is the product solving and how is that benefiting you?
TigerData allows us to efficiently store and analyze large volumes of time-series and relational data. It reduces query times, simplifies data management, and provides actionable insights, improving decision-making and operational efficiency
Great out of the box solution for any PostgreSQL user
What do you like best about the product?
Easy to start, easy to maintain, easy to scale
What do you dislike about the product?
Recent pricing model change is not ideal
What problems is the product solving and how is that benefiting you?
Allows to store and query large about of financial time series data
Good Service for good storage price
What do you like best about the product?
the functions that can be deployed inside the db's
What do you dislike about the product?
the flexibility in internal configurations
What problems is the product solving and how is that benefiting you?
it does offered a db with good functionalities like creating some cron jobs in it, or transformations.
Switched from AWS
What do you like best about the product?
Pricing compared with AWS is slightly better
What do you dislike about the product?
None (so far),
everything works fine as expected
everything works fine as expected
What problems is the product solving and how is that benefiting you?
Pricing and accessibility with ease of use as administrator
Great Vector Database Solution
What do you like best about the product?
The ease of set up with the pgai, pgvector, and pgvectorscale plugins makes setting up and running of a highly scalable vector database solution very quick and easy. They have good resources for beginers and advanced people alike and an active discord to help out user issues. The UI/UX of managing the databases are good and there is even a free month when just starting out.
The nodeJS implementation for postgres SDK is great, and the ability to write standard postgresql for queries and database managment makes this much more flexible and easier to manage than traditional vector databases.
I have used multiple vector databases and this is my faviout one so far for scalability. I use the UI every day when checking up on the health of my vector database and love the metrics it provides. It only took 1 development week to fully switch from a different Vector Database, but I have a massive codebase with a lot of functionality, I'm confident someone with a new codebase could integrate in a day.
The nodeJS implementation for postgres SDK is great, and the ability to write standard postgresql for queries and database managment makes this much more flexible and easier to manage than traditional vector databases.
I have used multiple vector databases and this is my faviout one so far for scalability. I use the UI every day when checking up on the health of my vector database and love the metrics it provides. It only took 1 development week to fully switch from a different Vector Database, but I have a massive codebase with a lot of functionality, I'm confident someone with a new codebase could integrate in a day.
What do you dislike about the product?
I think the UI can be very slow to load sometimes, especially when you have many tables, definetly could improve there. I also miss a vector Visializer like that of QDRANT.
What problems is the product solving and how is that benefiting you?
Scalable vector database with flexible quering, need I say more ;)
Great but can be costly for small hobby application
What do you like best about the product?
Reliability and ease of use and integration. Decent documentation
What do you dislike about the product?
The pricing. $50 per month for hobby project adds up.
What problems is the product solving and how is that benefiting you?
Time series based data storage and retrieval.
A great time series database with a great cloud offering
What do you like best about the product?
Product is very performant, cloud interface is easy to use but still offers a lot of control, Terraform provider makes setup a breeze and the team has been awesome
What do you dislike about the product?
Terraform provider not complete yet, missing some open source options to send cloud telemetry instead of Cloudwatch and Datadog
What problems is the product solving and how is that benefiting you?
Time series database for high performance ingress and egress for realtime dashboard monitoring
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