HOWEVER, they are not as "serverless" as you may think - pay-per-use, like Lambda. Yesterday AWS announced serverless versions of Kinesis, Redshift, and MSK (Kafka). If it does not have on-demand pricing nor turn off fully when idle, it is not serverless by most cloud observers' definition (which is also AWS's own definition when they invented serverless functions with Lambda). However, AWS's push towards "serverless" was soon criticized as only delivering auto-scaling capabilities rather than truly lifting infrastructural burdens off the customer.
#Aws athena vs snowflake plus#
Last year's focus was on adding serverless flavors of their analytical & streaming engines, plus on expanding their data marketplace features. (Not sure why MSK is missing while Kinesis is there.) This slide from the CEO keynote shows their sprawling data & analytics services. As for data movement, I am most focused on their data streaming capabilities (Kinesis and MSK) and serverless ETL service (Glue, to run Python/Spark). In particular, I am most focused on their data warehouse (Redshift), data lake query engine (Athena), and their AI/ML (SageMaker) and big data (EMR, to run Hadoop/Spark) analytical engines. Data & AnalyticsĪWS has been building up a set of capabilities around its data & analytics services, and continues to expand and cross-integrate across them. But their new Security Lake holds promise as a way to corral security analytics into S3 data lakes, and (despite competing with them) AWS continues to focus on co-sell with infrastructural partners like Snowflake and Databricks. I find Redshift is staying busy catching up to Snowflake's features while Snowflake moves farther forward.
While AWS focused heavily on Redshift enhancements and cross-service integrations, I was mostly underwhelmed.
Let's dive into the Data & Analytics product announcements and my thoughts on the impacts. (For instance, AWS Clean Rooms vs Amazon DataZone?) AWS has separate product teams and it shows, as there is no overarching plan at times, and often overlap and duplicative products. You don't seem to be able to decide whether you should use AWS or Amazon as your brand name for these products.
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