Amazon Athena Reviews & Product Details

What I like best about Amazon Athena is that it is very easy to use and fully serverless. We don’t need to manage any infrastructure, and we can directly query data stored in S3 using simple SQL. It saves time for data analysis and is very cost effective because we only pay for the data we scan. It also integrates well with other AWS services, which makes it very useful for analytics and reporting use cases Review collected by and hosted on G2.com.

One thing I dislike about Amazon Athena is that the cost can increase quickly if queries are not optimized properly, since pricing is based on data scanned. For large and unpartitioned datasets, it becomes expensive. Also, performance sometimes depends heavily on how well the data is structured in S3. It is not ideal for very low-latency or real-time analytics use cases. Query debugging can also be slightly difficult for beginners. Review collected by and hosted on G2.com.

What I value most is that it is serverless: it allows you to run standard SQL queries directly on data in Amazon S3, without having to provision infrastructure or move the information through ETL processes.

In practice, it is super useful for performing quick and ad-hoc exploratory analysis on Parquet or JSON files within our Data Lake. Additionally, by integrating natively with the AWS Glue Data Catalog, metadata management becomes almost transparent and much simpler. Review collected by and hosted on G2.com.

What I like the least is that the charge per TB scanned can become quite unpredictable if the queries are not well optimized (for example, when there are no partitions or compression is not used). A simple "SELECT" on a large dataset can turn out to be surprisingly expensive.

Additionally, performance drops significantly with the typical problem of many small files in S3 (small file problem), and that ends up forcing us to add extra compaction processes with AWS Glue to maintain efficiency.

And, finally, it is not the best option for low-latency reports or with high concurrency: in those scenarios, Redshift still performs better. Review collected by and hosted on G2.com.

It is easy to use Athena, whether you are a tech or a non-tech person. It has a very user-friendly interface, and the thing that I like the most is that you can query many types of source input data. Review collected by and hosted on G2.com.

I don't find it helpful when I need to query the data and make updates. Review collected by and hosted on G2.com.

Athena is a great fit when I need to run analysis on data stored in S3. Review collected by and hosted on G2.com.

It is cloud-native with respect to AWS. We need a solution that sits on top of the AWS cloud and also supports a multi-cloud setup. Review collected by and hosted on G2.com.

Amazon athena is very powerful serverless solution and it's very cost-effective. I like the user-friendly interface that athena provides to query data from any table present in the S3. I use athena to query data almost on a regular basis. The customer support is also very helpful with the queries regarding anything. It was very easy to implement because of very powerful documentation provided by AWS. Review collected by and hosted on G2.com.

There are very few things that I don't like about athena, like occasional lags when querying large datasets, there are also some features missing that could have helped the user a lot. Review collected by and hosted on G2.com.

Quick, powerful analytical tools. Uses familiar syntax. Uses S3 buckets to build the database. Allow several queries to be saved. Review collected by and hosted on G2.com.

Navigating AWS can be difficult at times. May not be as fast as some other solutions. Review collected by and hosted on G2.com.

I have worked on multiple databases so far. I found it to be better than traditional hive systems.

Within a minute the queries run for many gigabytes of storage.

On top of that, no need to have a system to run.

Since it is a service, anybody can login on web and see the data.

It predominantly helped me serve product people where they can tweak my query and do things on their own when usually I was involved everytime. Review collected by and hosted on G2.com.

I did not like some integration with languages like R. RJDBC package had some bugs. Review collected by and hosted on G2.com.

serverless architecture no requried infrastructure to manage.

pay only for what we queries we run, its make cost effecitve.

it supports major all the file formats example parquet, json, text and many more

we can integrate with aws glue service for ETL jobs.

due to serverless its more in performance. Review collected by and hosted on G2.com.

its less performance when we query on large datasets.

it has limited ETL functionalities when we compare to other services.

its highly dependent on s3 service. Review collected by and hosted on G2.com.

It is very easy, cost efficient and time saving solution to create ETLs, manage your metadata and quickly query from the untyped data present in S3 Review collected by and hosted on G2.com.

Amazon Athena should work on optimizing the process of running the query over big data. Sometimes, we have to use thrift servers just to query fast on big data.

Other point is error messages should be more precise. Review collected by and hosted on G2.com.

Pricing and ease to use, you can do queries of data with SQL syntax Review collected by and hosted on G2.com.

Not all SQL syntax allowed, you can't create tables from a query. Review collected by and hosted on G2.com.