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Serverless Databases: The Future of Event-Driven Architecture

133 点作者 marvinpinto超过 7 年前

12 条评论

hodgesrm超过 7 年前
&gt; I, personally, have seen many projects burning thousands a month in database costs because they prefer replicating the environment for testing branches.<p>If this is the premise for serverless database it&#x27;s a weak start. If you really need lightweight DBMS for testing just run MySQL or PostgreSQL in Docker. If you really need access to production-like data (e.g., a lot of it so you get realistic distributions) run the same DBMS on cheap hardware or cheap instances. In both cases you can use persistent volumes and shut down when things are not in use. Few people really care if it takes a few minutes to spin up the test environment.<p>As for the main point of Aurora offering a &quot;Serverless&quot; architecture it looks as if what they&#x27;ve really done is enabled the DBMS compute layer to scale up and down quickly. I wonder if this optimization fell out of pushing redo log management down into the storage layer. (See Section 3.1 <a href="https:&#x2F;&#x2F;www.allthingsdistributed.com&#x2F;files&#x2F;p1041-verbitski.pdf" rel="nofollow">https:&#x2F;&#x2F;www.allthingsdistributed.com&#x2F;files&#x2F;p1041-verbitski.p...</a> for details.)
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dsr_超过 7 年前
A comparison that only mentions pros and no cons is not a useful comparison. It&#x27;s a cheerleading piece.
jtwaleson超过 7 年前
We&#x27;re deploying thousands of tenants to their own postgres RDS instances which are completely overkill for most scenarios. On average we use about 3% CPU... We still do this because of three reasons: security isolation, performance isolation and monitoring. I think Aurora serverless will be a game changer for us, but we would still need per-tenant monitoring.
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peterevans超过 7 年前
I was hoping the future of event-driven architecture is that we would call it &quot;event-driven&quot; and not serverless; alas.
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moocowtruck超过 7 年前
databaseless serverless productless architecture
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manigandham超过 7 年前
This split of compute and storage into distinct layers is starting to become more common, and it has some pretty neat advantages like much better scalability and efficiency.<p>Google&#x27;s BigQuery and Snowflake Data are examples of data warehouses, similar to DIY presto&#x2F;drill&#x2F;spark on S3. Apache Pulsar brings that to messaging and distributed logs. It&#x27;ll be interesting to see how it applies to more OLTP database engines, although there are examples like TiDB which seem to work well enough.
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jimbokun超过 7 年前
“This isn’t the end, management teams are expecting lower resource costs and higher return on investment for the technology projects.”<p>Wow, really? Bit radical assertion there don’t you think? I thought they might want higher resource costs and lower returns on investment.<p>Maybe there is some good content in there, but I found it difficult to sift through the banalities to find out.
matchagaucho超过 7 年前
It makes me nervous when cloud companies release new features to select pilot groups.<p>The Aurora Serverless signup form asks no questions related to DB scale or capacity, so we&#x27;re left to assume they&#x27;re accepting pilot customers based on region or company size?
gregwebs超过 7 年前
There are other databases in this category.<p>Snowflake DB (data warehouse, so competes with Redshift rather than Aurora). Google&#x27;s other database offerings (Cloud Data Store and Big Query)
stunt超过 7 年前
DynamoDB has same properties but you will have more flexibility in Aurora Serverless.
M_Bakhtiari超过 7 年前
I still haven&#x27;t been able to find someone who can explain what make these elaborate layers of indirection running on servers in datacentres exactly &#x27;serverless&#x27;.
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arisAlexis超过 7 年前
isn&#x27;t this like Ethereum programming on a private blockchain?
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