11/16/2023 0 Comments Tableplus athena![]() ![]() ![]() >I'm sure some real workloads look like this, but I don't think it's a very good test case to show the strengths/weaknesses of an analytical databases query processor or query optimizer (no joins, unions, window functions, complex query shapes ?). > It looks like the queries are all single table queries with group-bys and aggregates over a reasonably small data set (10s of GB)? Plus, I want to direct people to the discussion generated when ClickBench was first posted to HN:Īs user AdamProut commented back at the time: We have to consider cases where certain databases may need to have testing suites that really capture their capabilities.ĬlickHouse themselves publishes a list of Limitations that everyone should keep in mind as they run ClickBench:ĬelerData (based on StarRocks) also wrote up this: But just like you had YCSB as a good general performance test, eventually a subset of users wanted something specific for Cassandra and Cassandra-like databases (DSE, ScyllaDB, etc.), so you eventually saw cassandra-stress. It is definitely a stab at getting an objective suite of tools for the real-time analytics space. Its results may or may not be applicable for guidance on the performance of your specific use case when you get to production. However, it's not the end-all, be-all of performance benchmarking and testing. All these functionalities can be accessed through a simple query.Full disclosure: I work at StarTree, which is powered by Apache Pinot.ĬlickHouse's ClickBench is a good general tool. Machine learning on the Athena platform can also be used for prediction regarding future events like trends and sales. These may be pre-built, bought from the AWS Marketplace or trained by the organization itself to detect interesting events and produce more natural insights. ![]() A smarter analysis made possible with learning algorithmsĪthena makes its querying exponentially smarter by integrating machine learning models in searches. Thus, the main technical knowledge required is that of SQL. The schema for the search is to be defined and then using popular SQL tools, the user needs to query for the required insights. ![]() Unlike other analytics tools, where management of convoluted ETL processes is absolutely essential, Athena users just need to enter the location of their data in the S3 storage system. Easy to use, and even easier to masterĪthena blows others out of the water with its high accessibility. The data related to the query is simply stored in the S3 storage system for low costs, so there is no requirement for any additional infrastructure. Amazon Athena doesn’t charge the business for the whole architecture it just charges them for each query run on the system. This, when coupled with the fact that it doesn’t require any server from the company’s part, makes it a reliable-cum-cheap solution for any size of business. The Athena system is designed to work with larger amounts of data and produce accurate query results in shorter periods of time. High ROI ensured along with higher accuracy and speeds It is also much easier to use than other analytics solutions. This powerful cloud-based data analytics platform has the capability to handle large queries and deliver results in a matter of seconds. Amazon has thus presented businesses with its own highly reliable web service called the Athena. Organizations, whatever services they provide, cannot function and thrive for long without the appropriate information and insights about the popularity of its services, latest trends in the market, the efficiency of its competitors and other such topics. Big data has become the operating system of the new generation. ![]()
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