Did I miss something huge?

Arguably the world's most popular database is Microsoft Excel.

If a customer's API was down, the event would go back on the queue with a header saying to retry it after some time. You can do some sort of incantation to specifically retrieve messages with a suitable header value, to find messages which are ready to retry. We used exponential backoff, capped at one day, because the API might be down for a week.

I didn't think of RabbitMQ as a database when I started that work, but it looked a lot like it by the time I finished.

But also no, RabbitMQ and Kafka and the like are clearly message buses and though they might also technically qualify as a DB it would be a poor descriptor.

Back when I worked in LA my CTO used to joke that most places use Microsoft Outlook as a database and Excel as BI tool.

[Source: I was friends with the guy who wrote it as well as other EToys employees. God that was a trainwreck.]

  a32c/4214/585e/9cb7/a554/74133a5fc986
    a32c/
      4214/
        585e/
          9cb7/
            a554/
              74133/a5fc986

Basically if you're manually scanning the heirarchy for anything but a consistency check or garbage collection you've already lost.

    18:35 $ tree .git/objects/
    .git/objects/
    ├── 02
    │   └── 9581d0c8ecb87cf1771afc0b4c2f1d9f7bfa82
    ├── 3b
    │   └── 97b950623230bd218cef6aebd983eb826b2078
    (...)
    ├── info
    └── pack
        ├── pack-b1fe2364423805afb6b1c03be0811c93b19dedc9.idx
        └── pack-b1fe2364423805afb6b1c03be0811c93b19dedc9.pack

    10 directories, 10 files

Would love to talk to anyone on the EToys team or anyone who has done something similar.

I'm @akamaozu on twitter.

I had to work on a tool that shows what's wrong with an assembly line: missing parts, delays, etc... So that management can take corrective action. Typical "BI" stuff but in a more industrial setting.

The company went all out on new technologies. Web front-end, responsive design, "big data", distributed computing, etc... My job was to use PySpark to extract indicators from a variety of data sources. Nothing complex, but the development environment was so terrible it turned the most simple task into a challenge.

One day, the project manager (sorry, "scrum master") came in, opened an excel sheet, imported the data sets, and in about 5 minutes, showed me what I had to do. It took me several days to implement...

So basically, my manager with Excel was hundreds of times more efficient than I was with all that shiny new technology.

That experience made me respect Excel and people who know how to use it a lot more, and modern stacks a lot less.

I am fully aware that Excel is not always the right tool for the job, and that modern stacks have a place. For example, Excel does not scale, but there are cases where you don't need scalability. An assembly line isn't going to start processing 100x more parts anytime soon, and one that does will be very different. There are physical limits.

The devil is in the details, and software is nothing but details. The product owner at the company I work for likens it (somewhat illogically, but it works) with constructing walls. You can either pick whatever stones you have lying around, and then you'll spend a lot of time trying to fit them together and you'll have a hell of a time trying to repair the wall when a section breaks. Or you can build it from perfectly rectangular bricks, and it will be easy to make it taller one layer at a time.

Using whatever rocks you have lying around is like building a prototype in Excel. Carefully crafting layers of abstraction using proper software engineering procedures means taking the time to make those rectangular bricks before building the wall. End result more predictable when life happens to the wall.

Unfortunately which specific features of Excel are acceptable to remove are unknown until you have already way over invested into the project.

The best I've seen this done is having Excel as a client for your data store. Where read access is straightforward and write can be done via csv upload (and heavy validation and maybe history rollback).

That way the business can self-service every permutation of dashboard/report they need and only when a very specific usecase arises do you need to start putting engineering effort behind it.

I suppose you can also supplement the Excel workflow with a pared down CRUD interface for the inevitable employee allergic to excel.

Here is another option that we use instead of CSV import.

Our applications support custom reports and custom fields.

Users can define new reports and run them on demand.

They can also define custom field types with validation, data entry support, etc.

This combination provides some of the extensibility of Excel while retaining the advantages of an application.

Edited for wording changes.

[0] https://news.ycombinator.com/item?id=23292374

You can complain about their solution or see it as an opportunity.

I posted elsewhere[0] in this thread about my employer's practice of replacing shared spreadsheets with web applications.

This approach works quite well for us and I would encourage you to consider it as an option.

[0] https://news.ycombinator.com/item?id=23292374

Confluent, the company behind Kafka, are 100% serious about Kafka being a database. It is however a far better database than MongoDB.

Many of my employer's applications started out as a shared spreadsheet or Access database.

Our development team worked with the users and built a web application to solve the same problem.

This approach has a lot of advantages:

* The market exists and has an incumbent. There's a lower risk of a write-off.

* The users are open to process changes. You still have to migrate people off of the spreadsheet, though.

* It's easy to add value with reporting, error checking, concurrent access, and access control.

* You can import the existing data to make the transition easier. This will require a lot of data cleaning.

Edited to add the following text from another post.

You can cover most of the requirements with a set of fixed fields.

The last 10% to 20% of the use cases requires custom reports and custom fields.

Users should be able to define their own reports and run them without your involvement.

They should also be able to define custom field types with validation, data entry support, etc.

If your web application has these two features and other advantages then you should be able to replace Excel.

ksqldb is actually a database on top of this.

The thing is that they have an incrementally updated materialized view that is the table, while the event stream is similar to a WAL ("ahead of write logs?" in this case).

Because eventually you can't just go over your entire history for every query.

It used to be that bargain basement shared-hosting providers would only give you a LAMP stack, so it was MySQL or nothing. But if you're on RDS, Postgres every time for my money.

It's really sad because all the contributors to Postgres have made an AMAZING database that's such a joy to work with. And then there's PgAdmin4 where its almost like they just don't care...

I don't feel I'm smart enough to contribute anything to PgAdmin4 to try make it better. So I stick to DataGrip and DBeaver.

For MySQL, I haven't found anything that beats SequelPro. For Postgres, I haven't found anything that comes close to parity, but my favorite is Postico.

I know people that swear by IntelliJ for their db stuff, it just never hit home for me personally though.

It’s the only DB client that doesn’t look like it was built in the 90’s. Slick UX & UI. Nice balance between developer tool & admin tool

I can't compare against SequelPro as I don't have a Mac, but DBeaver's worth a try for anyone looking for a cross platform DB editor

I'd probably choose Postgres over MySQL for a new project just to have the improved JSON support, but there's upsides to MySQL too:

- Per-thread vs per-process connection handling

- Ease of getting replication running

- Ability to use alternate engines such as MyRocks

You can’t cut corners like that without inviting questionS about the character of the primary committers. The pecking order in software is about trust.

People don’t let that stuff go easily, which is why you still see people harping on MongoDB. Once someone is labeled a liar And a cheat, everything they say that doesn’t add up is “guilty until proven innocent.”

The utf-8 situation is on top of a bed of half truths. Things like publishing benchmarks with backends that don’t support isolation. A cornerstone of a good DB is handling concurrent access efficiently and correctly. Drawing attention to other benchmarks is a lie by omission. Better than just being incorrect for a decade, certainly, but still sketchy.

Though I'm willing to put up with it due to its incredible compression capabilities...

[0]: https://jira.mariadb.org/browse/MDEV-22609

Oracle is great if and only if you have a use case that fits their strengths you have an Oracle specific DBA, and you do not care about the cost. I have been on teams where we met those criteria, and I genuinely had no complaints within that context.

Every time I need to work with an Oracle DB it costs me weeks of wasted time.

For a specific example, I was migrating a magazine customer to a new platform, and all of the Oracle dumps and reads would silently truncate long textfields... The "Oracle experts" couldn't figure it out, and I had to try 5 different tools before finally finding one that let me read the entire field (it was some flavor of JDBC or something). To me, that's bonkers behavior, and is just one of the reasons I've sworn them off as anything other than con artists.

I gotta say, as much as I hate it with a passion, and as often as it breaks for seemingly silly reasons (so many deadlocks), it's at least tolerable (even if I feel like Postgres is better by just about every metric).

I'm familiar with the variant, "InfoSec won't let us deploy a DB on the same host".

  sqlite> create table foo (n int);
  sqlite> insert into foo (n) values ('dave');
  sqlite> select count(*) from foo where n = 'dave';
  1

SQLite does not use column typing except in integer primary keys.

I think most people have realised weak typing is not a good idea in programming languages. It’s especially not a good idea in databases.

> As far as we can tell, the SQL language specification allows the use of manifest typing. Nevertheless, most other SQL database engines are statically typed and so some people feel that the use of manifest typing is a bug in SQLite. But the authors of SQLite feel very strongly that this is a feature. The use of manifest typing in SQLite is a deliberate design decision which has proven in practice to make SQLite more reliable and easier to use, especially when used in combination with dynamically typed programming languages such as Tcl and Python.

It's intended behavior that's compatible with the SQL spec.

The big issue is that sqlite does full db locking for any operation, so during any write you can't just easily read at all.

This can be fixed with WAL mode, but WAL mode is broken in uts early versions, and new versions of sqlite aren't in all disteos yet, despite being out for almost a decade. And even WAL mode gets abysmal performance.

Definitely would not use in a read/write situation for a web API for various reasons, though. :-)

They have their own layer on top that happens to use SQLite as the storage format on disk[1]. This layer means they aren't using full SQLite at the application level, but rather using their custom database in the application, and SQLite within their custom database.

Further, they've customised the SQLite codebase as far as I can tell to remove much of the functionality that SQLite uses to ensure that multiple instances can safely edit the same file on disk together, then they memory map the file and just have many threads all sharing the same data.

[1]: FoundationDB also does this, and scales to thousands of nodes. The trick is that it's essentially _many_ separate, very simple SQLite databases, each being run independently.

I can tell you this emphatically as I spent 6 months trying to eke out performance with MySQL (5.6). PostgreSQL (9.4) handled the load much better without me having to change memory allocators or do any kind of aggressive tuning to the OS.

MySQL has some kind of mutex lock that stalls all threads, it's not noticeable until you have 48cores, 32 databases and a completely unconstrained I/O.

EDIT: it was PG 9.4 not 9.5

They were both the latest and greatest at the time

> redo the benchmark today and I’ll be surprised if you come to the same results.

I would, but it was not just a benchmark, it was a deep undertaking including but not limited to: optimisations made in the linux kernel, specialised hardware along with custom memory allocators and analysing/tracing/flamegraphing disk/memory access patterns to find hot paths/locks/contention. (and at different scales: varying the number of connections, transactions per connection, number of databases, size of data, etc)

It was 6 months of my life.

> PGsql even has a wiki page where they discuss implementing MySQL features and changing their architecture so they can scale.

Just because mysql has some good ideas doesn't mean it scales better. I know for a fact that it didn't in 2015. I doubt that they have fixed the things I found, I could be wrong. But it would have to be a large leap forward for MySQL and PostgreSQL has had large performance improvements since then too.

also, I read that page and it talks nothing about scaling, just that some storage drivers have desirable features (memory tables are very fast, and PGSQL doesn't support it; archive tables are useful for writing to slower media, you can do this with partitioning but it's not intuitive)

yes, I should run the test again, but it was 6 months of my life, and I don't see how much could have changed.

Logical replication or synchronous multimaster replication may meet your needs.

Almost none of is remotely accurate e.g. RabbitMQ isn't even a database.

It may be good idea to take a break from the computer and find something less stressful to do.

[0] https://www.confluent.io/blog/okay-store-data-apache-kafka/

[1] https://dzone.com/articles/is-apache-kafka-a-database-the-20...

The fact that you put Kafka and RabbitMQ in the same category sort of makes me feel like you're out of your element, Donnie.

We use it for a very specific use case and its been perfect for us when we need raw speed over everything. Data loss is tolerable.