Reviews from AWS Marketplace
0 AWS reviews
-
5 star0
-
4 star0
-
3 star0
-
2 star0
-
1 star0
External reviews
External reviews are not included in the AWS star rating for the product.
Good Product, Good Support, Bad Account Management
What do you like best about the product?
the platform and the features that has been developed
What do you dislike about the product?
After the account manager has changed, I rarely got answers from them whenever I asked questions. Probably because we are small customer, however I just need as simple answer as "yes" or "no" (we are not pushing to develop some features, just want to explore every possibilities that we could have with this platform) but then what I got is just "hold on we will come back to you" and yet never comeback with any answers.
What problems is the product solving and how is that benefiting you?
big data platform management, analytics and business intelligence, Extract Transform Load . I realized that those things are hard to tackle by ourselves so we decided to get help from third party that has a lot of capabilities
- Leave a Comment |
- Mark review as helpful
Connects all of our data
What do you like best about the product?
The team at Treasure Data is a pleasure to work with. They are accommodating and go out of their way to make sure we're using their solution to the best of its ability.
What do you dislike about the product?
Nothing - we are very happy with the service.
What problems is the product solving and how is that benefiting you?
With Treasure Data, we are able to connect data from our platform to our marketing and sales automation tools, as well as our customer success and community platforms. From these connections, we are able to draw actionable insights and launch marketing programs to the right targets at the right time.
Excellent Platform for Big Data Solution
What do you like best about the product?
- Flexible infra
- Powerful hive environment
- Real-time and super helpful customer service
- Powerful hive environment
- Real-time and super helpful customer service
What do you dislike about the product?
- Presto implementation isn't very smooth
What problems is the product solving and how is that benefiting you?
- Flexible data pipeline process with Python or CML
- We use it for all our live data or analytical layer
- We use it for all our live data or analytical layer
Recommendations to others considering the product:
- This is definitely a very powerful big data and business intelligence platform
- Very friendly to startups and data analysts, as well as software engineers
- Smooth connection to production system as well as internal analytics tools like tableau, AWS redshift, or even looker
- High quality and very helpful real time customer support
- Very friendly to startups and data analysts, as well as software engineers
- Smooth connection to production system as well as internal analytics tools like tableau, AWS redshift, or even looker
- High quality and very helpful real time customer support
Treasure Data Review
What do you like best about the product?
It saves queries so they can be reused in the future.. The API is pretty fast when downloading relatively sizeable amounts of data.
What do you dislike about the product?
When I'm inspecting a table, and I want to query it, the UI forces me to go through an unnatural path. There should be a button to query a table from the table page (maybe writing a SELECT * FROM table ?).
When I download data through the API, there should be a way to get the names of the columns that are being pulled. In some instances, the tuples have 100+ items, and I've had to download the query in a different way just to get the names of the columns and paste them in the interpreter to build a "dictionary" between indices and columns
When I download data through the API, there should be a way to get the names of the columns that are being pulled. In some instances, the tuples have 100+ items, and I've had to download the query in a different way just to get the names of the columns and paste them in the interpreter to build a "dictionary" between indices and columns
What problems is the product solving and how is that benefiting you?
It's our main source for logging. It is also the intermediate step between our production DB and the DB that our less technical users have access to.
From 0 to analyze in a week
What do you like best about the product?
Powerful toolbox backed by a solid user support experience and available updated documentation.
What do you dislike about the product?
the lack of advance tags, filtering and search option for queries (database of origin, type of output, output name, custom tags ...)
What problems is the product solving and how is that benefiting you?
Centralizing and normalizing multiple data stream in a central location while having enough power to run queries in single digit minutes.
Recommendations to others considering the product:
Make sure you have an exhaustive list of all the required data source to connect and validate the aggregation level supported by each API
Treasure Data allowed my team to build quick and flexible big data pipelines
What do you like best about the product?
Flexible schema on read data storage, quick and robust data ingestion with fluentD and embulk, integratjons with data science tools such as R and Python Pandas, Presto and Hive support and Google tag manager integration to track users behaviour. Great support.
What do you dislike about the product?
Limited support with Python Luigi workflow magement solution, although they offer alternative solution called dig dag which might be even better. Admin dashboard could be improved to see data limits based on existing contract so that you can manage better data ingestion and avoid going above limit. More concrete business cases and mkre technical examples on how to design pipelines in hive or presto would be useful.
What problems is the product solving and how is that benefiting you?
Big Data pipeline to get insight for the business and generate report in Shiny.
Storing unstructured data which are then pulled using Python Pandas to train and test machine learning solutions used in the company.
Treasure data Google tag manager integration to build marketing attribution models and support product analytics.
Storing unstructured data which are then pulled using Python Pandas to train and test machine learning solutions used in the company.
Treasure data Google tag manager integration to build marketing attribution models and support product analytics.
Great technology to get an ETL pipeline up and running quickly
What do you like best about the product?
The flexibility and power of the platform
What do you dislike about the product?
Ease of misuse if used improperly. Its easy to clog your job queue if you are using up your workers on calculation queries rather than exporting the raw to your warehouse and querying it there. Still trying to retrain team-members on this concept >.<
What problems is the product solving and how is that benefiting you?
ETL pipeline for real-time analytics data
Recommendations to others considering the product:
TD is best used an ETL pipeline not a scheduled query interface. Export results to a warehousing database for scheduled queries or you will clog your job pipeline
Decent out of the box solution, but benefits degrade as table size grows
What do you like best about the product?
The ease of set-up and how the data flows in almost live.
What do you dislike about the product?
Querying data on large table takes forever, plus everything flows into one table, which expands indefinitely and data cannot be archived or table shrunk in any way.
What problems is the product solving and how is that benefiting you?
Getting event level data from our mobile games.
Recommendations to others considering the product:
Decent for companies with small to medium data tables.
Comprehensive data analytics platform
What do you like best about the product?
Treasure Data is packaging several powerful open source software very well and providing it with amazing customer support. Their product is easy to use and almost maintenance free, but if I have a problem, their customer support helps me to solve the problem almost 24/7.
What do you dislike about the product?
Since their product is open-source based, their documentation is old or incomplete often times. Also, they are upgrading their system very frequently, but not providing the release note each time. It's fine as long as their change doesn't cause any issues, but once it causes an issue, it's very frustrating to figure out the root cause of the issue without the release note.
What problems is the product solving and how is that benefiting you?
We hit the capacity limit of the relational database and migrated our data analytics platform to Treasure Data. Since Treasure Data is providing tons of data connectors, the migration was smooth. Also, it's super easy to feed more data from 3rd party software such as Zendesk to Treasure Data.
We don't have to have a dedicated data engineer in Analytics team because Treasure Data is almost maintenance free.
We don't have to have a dedicated data engineer in Analytics team because Treasure Data is almost maintenance free.
Recommendations to others considering the product:
Treasure Data is very powerful data analytics platform which is coming with a comprehensive toolset such as data connector, bulk importer, and workflow engine. Also, their customer support is amazing. I highly recommend it!
Awesome querying tool for tecg
What do you like best about the product?
Very fast querying large datasets. TD utilizes their unique time parsing of tables to achieve this.
What do you dislike about the product?
Some of the user defined functions are fairly different, especially the date parsing and date operation functions. These might take a little effort to get used to.
What problems is the product solving and how is that benefiting you?
We have done a lot of user path analysis and event sequence analysis that we're impossible to do in MySQL with the datasets are large as ours. We would had to do a bunch of self joins but the window functions in presto combined with powerful engine made these analysis painless.
showing 141 - 150