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AWS DynamoDB: the cost of indexes

By Franck Pachot

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That’s common to any data structure, whether it is RDBMS or NoSQL, indexes are good to accelerate reads but slow the writes. This post explains the consequences of adding indexes in DynamoDB.

AWS DynamoDB Local: running NoSQL on SQLite

By Franck Pachot

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DynamoDB is a cloud-native, managed, key-value proprietary database designed by AWS to handle massive throughput for large volume and high concurrency with a simple API.

RDBMS (vs. NoSQL) scales the algorithm before the hardware

By Franck Pachot

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In The myth of NoSQL (vs. RDBMS) “joins dont scale” I explained that joins actually scale very well with an O(logN) on the input tables size, thanks to B*Tree index access, and can even be bounded by hash partitioning with local index, like in DynamoDB single-table design. Jonathan Lewis added a comment that, given the name of the tables (USERS and ORDERS). we should expect an increasing number of rows returned by the join.

In this post I’ll focus on this: how does it scale when index lookup has to read more and more rows. I’ll still use DynamoDB for the NoSQL example, and this time I’ll do the same in Oracle for the RDBMS example.

DBPod – le podcast Bases de Données

By Franck Pachot

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J’essaie quelque chose de nouveau. Je publie beaucoup en anglais (blog, articles, présentations) mais cette fois quelque chose de 100% francophone. En sortant du confinement, on reprend les transports (train, voiture,…) et c’est l’occasion de se détendre en musique mais aussi de s’informer avec des podcasts. J’ai l’impression que c’est un format qui a de l’avenir: moins contraignant que regarder une video ou ou lire un article ou une newsletter. Alors je teste une plateforme 100% gratuite: Anchor (c’est un peu le ‘Medium’ du Podcast).

What is a serverless database?

By Franck Pachot

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After reading the https://cloudwars.co/oracle/oracle-deal-8×8-larry-ellison-picks-amazons-pocket-again/ paper, I am writing some thoughts about how a database can be serverless and elastic. Of course, a database needs a server to process its data. Serverless doesn’t mean that there are no servers.

Oracle Standard Edition on AWS ☁ socket arithmetic

By Franck Pachot

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Note that I’ve written previously about Oracle Standard Edition 2 licensing before but a few rules change. This is written in May 2020.
TL;DR: 4 vCPU count for 1 socket and 2 sockets count for 1 server wherever hyper-threading is enabled or not.

The SE2 rules

I think the Standard Edition rules are quite clear now: maximum server capacity, cluster limit, minimum NUP, and processor metric. Oracle has them in the Database Licensing guideline.

2 socket capacity per server

Oracle Database Standard Edition 2 may only be licensed on servers that have a maximum capacity of 2 sockets.

The myth of NoSQL (vs. RDBMS) agility: adding attributes

By Franck Pachot

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There are good reasons for NoSQL and semi-structured databases. And there are also many mistakes and myths. If people move from RDBMS to NoSQL because of wrong reasons, they will have a bad experience and this finally deserves NoSQL reputation. Those myths were settled by some database newbies who didn’t learn SQL and relational databases. And, rather than learning the basics of data modeling, and capabilities of SQL for data sets processing, they thought they had invented the next generation of persistence… when they actually came back to what was there before the invention of RDBMS: a hierarchical semi-structured data model. And now encountering the same problem that the relational database solved 40 years ago. This blog post is about one of those myths.

AWS Aurora vs. RDS PostgreSQL on frequent commits

This post is the second part of https://blog.dbi-services.com/aws-aurora-xactsync-batch-commit/ where I’ve run row-by-row inserts on AWS Aurora with different size of intermediate commit. Without surprise the commit-each-row anti-pattern has a negative effect on performance. And I mentioned that this is even worse in Aurora where the session process sends directly the WAL to the network storage and waits, at commit, that it is acknowledged by at least 4 out of the 6 replicas. An Aurora specific wait event is sampled on these waits: XactSync. At the end of the post I have added some CloudWatch statistics about the same running in RDS but with the EBS-based PostgreSQL rather than the Aurora engine. The storage is then an EBS volume mounted on the EC2 instance.

AWS Aurora IO:XactSync is not a PostgreSQL wait event

By Franck Pachot

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In AWS RDS you can run two flavors of the PostgreSQL managed service: the real PostgreSQL engine, compiled from the community sources, and running on EBS storage mounted by the database EC2 instance, and the Aurora which is proprietary and AWS Cloud only, where the upper layer has been taken from the community PostgreSQL. The storage layer in Aurora is completely different.