[HN Gopher] AWS Redshift Serverless
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       AWS Redshift Serverless
        
       Author : Trisell
       Score  : 52 points
       Date   : 2021-11-30 17:51 UTC (5 hours ago)
        
 (HTM) web link (aws.amazon.com)
 (TXT) w3m dump (aws.amazon.com)
        
       | bryan0 wrote:
       | How is this different than Athena?
        
         | glogla wrote:
         | Two competing departments inside AWS.
         | 
         | Technically, Athena is based on modified Presto while Redshift
         | is (very) heavily modified Postgres.
        
           | the_af wrote:
           | Competing departments and competing underlying technologies.
           | Postgres (and therefore Redshift) is running a relational
           | database engine under the hood.
        
             | glogla wrote:
             | Yes, though with ra3 storage being on S3, I think they are
             | getting more and more similar.
        
         | tyingq wrote:
         | Query things other than data in S3 seems to be the big
         | difference.
        
           | bdcravens wrote:
           | Athena can query non-s3 data sources using federated query.
        
             | the_af wrote:
             | But that's not to say it's the best idea. Athena is mostly
             | for S3; AWS say so.
             | 
             | From their FAQ [1]:                   Q: What is the
             | difference between Amazon Athena, Amazon EMR, and Amazon
             | Redshift?              [...] Amazon Redshift provides the
             | fastest query performance for enterprise reporting and
             | business intelligence workloads, particularly those
             | involving extremely complex SQL with multiple joins and
             | sub-queries.              [...] Amazon Athena provides the
             | easiest way to run ad-hoc queries for data in S3 without
             | the need to setup or manage any servers.
             | 
             | Elsewhere they also recommend Athena for unstructured data.
             | This and a relational database like Postgres are
             | fundamentally different and you shouldn't use one when your
             | use case is primarily meant for the other.
        
         | the_af wrote:
         | Athena is not a relational database under the hood. Very
         | different technologies with different implications.
        
         | tmitchel2 wrote:
         | My impression is
         | 
         | Athena = Lambda + S3 (what i would call true serverless)
         | 
         | Redshift Serverless = Auto AWS Managed EC2 instances with local
         | storage + S3
         | 
         | Although I could be wrong as I just had a quick 5 minute look
         | at it...
        
       | bayan1234 wrote:
       | I was initially excited about this as I think it might solve our
       | Redshift pain points and potentially avoid us having to deal with
       | a migration to Snowflake but then I remembered when AWS account
       | managers promised Athena and Spectrum would solve these same
       | problems at a previous company I worked for a few years ago. I'm
       | assuming the developer experience will still be terrible with
       | lots of knobs to tune to actually get any decent
       | cost/performance.
        
       | dreyfan wrote:
       | > Just load your data
       | 
       | Load my data where? This is "serverless".
        
         | the_af wrote:
         | To "the cloud" :P
         | 
         | More seriously, "serverless" usually just means you aren't
         | supposed to worry about server/cluster management, not that
         | there are no servers anywhere. So it really means "load your
         | data to Redshift, wherever that lives".
        
           | dreyfan wrote:
           | I look forward to the next stage of cloud hype - dataless -
           | so I don't have to worry about the nuances of data management
           | and I can just run my analytics.
        
             | antod wrote:
             | I've long dreamed of that. Everything becomes stateless and
             | everything to do with GDPR/PCI/Disaster
             | recovery/anonymisation/performance/scaling/etc/etc becomes
             | so much easier.
        
       | orf wrote:
       | We've just moved to Snowflake. I haven't really been impressed
       | with some of the new features added to Redshift, it seems like
       | too little and too late.
       | 
       | The JSON support (SUPER type) is kind of cool, and they are
       | moving towards more "automatic" sorting + partitioning, but it's
       | just all a bit shit to be honest.
       | 
       | We encountered major bugs with data-sharing, our clusters keep
       | insisting that zstd is the best compression format to use for all
       | our data (but then never actually using it), materialised views
       | often fail to update and understanding why is a nightmare,
       | terrible performance if your strings are varchar(max) (guess what
       | Glue sets them to...), Redshift data often just dies (4 hour
       | downtime recently, no status page) and has some really weird
       | semantics around listing queries, before the data API you
       | couldn't run async queries and it's eventbridge integration
       | straight up doesn't work, nightmare bugs in the Java connection
       | library that don't show up using psql, tiny set of types (no
       | arrays, uuids), unkillable queries, AQUA actually causing
       | everything to slow down hugely, critical release notes posted
       | only in a fucking random forum, etc etc.
       | 
       | Snowflake has apparently sorted this, as well as including
       | ingestion tools (snowpipe) that you'd otherwise have to stitch
       | together with AWS Glue or something (a cursed service if ever
       | there was one).
       | 
       | That being said, in some cases Redshift absolutely flies. But the
       | real world isn't filled with ideal schemas and natural sort keys.
       | It's messy. And Snowflake deals with messy better.
        
         | b9a2cab5 wrote:
         | I've had terrible experiences with Snowflake "automatic"
         | optimizations. You have zero visibility or control over
         | partitioning, join strategy, or anything else compared to
         | Spark/Databricks.
        
           | dominotw wrote:
           | > You have zero visibility or control over partitioning
           | 
           | snowflake give you visiblity into clustering [1] and in the
           | query profile view you can see how pruning is working( or not
           | working)
           | 
           | Can you give an example of what you visibility you would like
           | to see in terms of partitioning?
           | 
           | 1. https://docs.snowflake.com/en/sql-
           | reference/functions/system...
        
         | dominotw wrote:
         | given snowflake also uses s3. Could aws do something with
         | redshift that moves computation closer to s3 and be even faster
         | than snowflake. Basically take advantage of the fact that they
         | own s3.
        
           | dalyons wrote:
           | they already have
           | https://aws.amazon.com/redshift/features/aqua/
           | 
           | basically distributing compute down to the actual storage
           | nodes
        
             | orf wrote:
             | Yeah that's cool except it made all our queries slower.
             | I'll add that to my list above, forgot about that.
        
         | ggregoire wrote:
         | What do you mean "too late"? Redshift was released in 2012.
         | 
         | Edit for future readers: the original comment was "I haven't
         | really been impressed with Redshift, it seems like too little
         | and too late".
        
           | orf wrote:
           | Sorry, I tend to abbreviate too much. Given the context of
           | the article (new sexy cool redshift features ripped from
           | Snowflake) I meant to convey "the direction redshift is
           | heading in seems too little too late".
        
             | ggregoire wrote:
             | Oh ok. I don't know Snowflake so I had no idea this new
             | feature was a (late) response to Snowflake.
        
           | NikolaeVarius wrote:
           | This article was released 30 NOV 2021. So 9 years,
        
       | ndm000 wrote:
       | I have worked with several companies that have their
       | infrastucture on AWS but consider BigQuery or Snowflake for the
       | serverless model they provide. This brings RedShift much closer
       | to those options. I envision Redshift Serverless becoming the
       | default options for most enterprises, mainly because it stays in
       | the AWS ecosystem and you don't have to work with a different
       | vendor and create different cost governance processes.
       | 
       | I beleive the real advantage AWS has here is in cost. Snowflake
       | has positioned itself as price competitive with Redshift but this
       | is primarily due to Snowflake's ability to scale on-demand,
       | whereas prior Redshift versions required you to size for peak
       | usage (RA3 helped with this). In my experience Snowflake is an
       | order of magnitude more expensive if you compare similiar
       | workloads and do not account for idle time. We will need to see
       | the performance of a "Redshift Processing Unit" to be sure of the
       | advantage, but even so AWS will be able provide significant
       | downward cost pressure through this offering.
        
         | ignoramous wrote:
         | > _In my experience Snowflake is an order of magnitude more
         | expensive if you compare similiar workloads and do not account
         | for idle time._
         | 
         | Cost reasons is why I'm most bullish about DataBricks's FOSS
         | https://delta.io
        
       | spullara wrote:
       | I wish Amazon would stop naming things "serverless" that clearly
       | have a well defined type and number of servers at any point. That
       | includes Redshift Serverless and Aurora Serverless. If it has a
       | cluster, it isn't serverless it is just autoscaling. Every time
       | they announce a serverless product I'm assuming that it will be
       | like Lambda and am mostly disappointed. For example, a real
       | Aurora Serverless would be more like CockroachDB Cloud or
       | DynamodDB. And a real Redshift Serverless would be more like
       | BigQuery.
        
       | ggregoire wrote:
       | It's not very clear why I should keep using a normal Redshift
       | instead of switching to Serverless? Anyone has more insights?
        
         | bayan1234 wrote:
         | If you have a very stable SQL pipeline that runs frequently
         | during the day then it's probably cheaper to have it on a
         | normal Redshift cluster.
        
       | opjjf wrote:
       | So basically BigQuery from AWS. Looks good on first sight, a bit
       | late. Personally worked for a large org which has just moved from
       | BigQuery from Redshift and I have to say that BigQuery is the
       | much better product.
        
         | glogla wrote:
         | Yeah I get that they want to go after Snowflake, Databricks and
         | BigQuery, but AWS it not known for delivering high quality
         | software. They have few things that are very good (EC2, S3,
         | Lambda) and the rest is done by their B-team and barely holding
         | together.
        
           | fdgsdfogijq wrote:
           | Keep telling yourself that
        
         | pram wrote:
         | Athena is BigQuery from AWS. I'd have to imagine this is for
         | people already heavily invested in Redshift.
        
           | tedivm wrote:
           | Athena is not BigQuery. Athena is just a fancy wrapper around
           | Hive (you can see this right from the log output) and just
           | runs map reduce over your S3 data. It's a great tool for what
           | it is.
           | 
           | BigQuery is a full database. It is _significantly_ faster
           | than running anything from Athena. The closest comparison on
           | AWS is Redshift.
        
             | mdasen wrote:
             | I think Athena has a lot of value (especially given its
             | pricing), but you're not wrong that it has limitations.
             | 
             | Getting data into Athena isn't something that is just done
             | for you. Athena just takes what you've put on S3 and
             | queries over it - and leaves getting it onto S3 (and into
             | an efficient format) as an exercise for the reader.
             | 
             | Athena's speed varies a lot depending on what format you
             | put things in. Querying over CSVs will mean that you're
             | slow and reading a lot of data. Querying over ORC (column-
             | store) files is pretty quick.
             | 
             | The big thing is Athena's pricing. They price it on how
             | much data you read _in reality_ not how much data would be
             | read if things weren 't optimized. BigQuery charges you
             | based on how much data would be read if it weren't
             | optimized. With BigQuery, an integer is always 8 bytes. It
             | doesn't matter if they're able to optimize it down to
             | nothing using RLE (run length encoding). You still pay the
             | full 8 bytes. If your ORC files make that integer column
             | tiny, you get the benefit of that.
             | 
             | BigQuery is great, but Athena's pricing is a lot cheaper
             | given that you get to benefit from any storage optimization
             | you do.
             | 
             | Out of curiosity, how have you used Athena that you're
             | seeing it be so much slower? In my experience, BigQuery is
             | faster (maybe 2x faster), but I've been using column-
             | oriented data with Athena. If you're using CSVs with
             | Athena, it will be way slower than BigQuery.
             | 
             | I'm always a little surprised that AWS doesn't build Athena
             | out more, but I guess if they did they'd want money and
             | margin for the value add. Still, Athena is a pretty decent
             | serverless Presto and Presto can work pretty well over data
             | in column formats.
        
             | ideonode wrote:
             | Athena is more of a wrapper over Presto / Trino than Hive.
             | It does not run map reduce per se over your data - its a
             | SQL engine.
        
               | pdelgallego wrote:
               | AWS Glue Data catalog is Hive, and as you mentioned,
               | Athena is a wrapper of Presto
        
         | spullara wrote:
         | It isn't. It is more similar to Snowflake's warehouse model.
        
         | tedivm wrote:
         | The only problem with BigQuery is that it's on GCP, so either
         | you have to migrate your whole workload over or you end up
         | eating a lot of data transfer costs.
         | 
         | Having used both I do think BigQuery is better in a lot of ways
         | (although it's easier to make it a lot expensive too), but I'm
         | really excited to see Redshift catch up. Adding the serverless
         | options are really great too since my biggest complaint with
         | Redshift was managing the quantity and type of the underlying
         | instances.
        
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