SQLx is a modern SQL client built from the ground up for Rust, in Rust.
Truly Asynchronous. Built from the ground-up using async-std using async streams for maximum concurrency.
Type-safe SQL (if you want it) without DSLs. Use the
query!()macro to check your SQL and bind parameters at compile time. (You can still use dynamic SQL queries if you like.)
Pure Rust. The Postgres and MySQL/MariaDB drivers are written in pure Rust using zero unsafe code.
This is like JS Fiddle, but for SQL. Pick from MySQL, Postgres, or SQLite. Then load up some queries, run them, and share with others. Super cool 👍
Our approach comes from low-latency trading; QuestDB’s stack is engineered from scratch, zero-GC Java and dependency-free.
QuestDB ingests data via HTTP, PostgresSQL wire protocol, Influx line protocol or directly from Java. Reading data is done using SQL via HTTP, PostgreSQL wire protocol or via Java API. The whole database and console fit in a 3.5Mb package.
According to the great knowledge base in the sky, NewSQL is, “a class of relational database management systems that seek to provide the scalability of NoSQL systems for online transaction processing workloads while maintaining the ACID guarantees of a traditional database system.”
In an effort to make my team write better SQL, I went over reports written by non-developers and code reviews, and gathered common mistakes and missed optimization opportunities in SQL.
Dividing integers, accidentally counting nullable columns, column position in
GROUP BY and
ORDER BY, and 9 other common gotchas. Don’t get got!
Mat, Johnny, and Jaana are joined by Francesc Campoy to talk about Graph databases. We ask all the important questions — What are graph databases (and why do we need them)? What advantages do they have over relational databases? Are graph databases better at answering questions you didn’t anticipate? How is data structured? How do queries work? What problems are they good at solving? What problems are they not suitable for? And…since we had Francesc on the hot seat, we asked him about Just for Func and when it’s coming back.
One question I ask a lot of folks I interview is what
$PROJECT_X looks like three to five (sometimes 10) years from now. Very few people answer that question without some hemming and hawing.
Enter Andy Pavlo, Associate Professor of Databaseology at Carnegie Mellon, throwing his hat in the ring on the future of databases 50 years (!) from now:
The role of humans as database administrators will cease to exist. These future systems will be too complex for a human to reason about. DBMSs will finally be completely autonomous and self-healing. Again, the tighter coupling between programming frameworks and DBMSs will allow the system to make better decisions on how to organize data, provision resources, and optimize execution than human-generated planning.
That is just one of roughly eight things Andy predicts. Fun to think about, if nothing else.
This week, I wrote a shopping cart to sell my books directly from my own site. So I took a couple extra hours today to put my code into public view, so anyone can play around with it.
osquery exposes an operating system as a high-performance relational database. This allows you to write SQL queries to explore operating system data. With osquery, SQL tables represent abstract concepts such as running processes, loaded kernel modules, open network connections, browser plugins, hardware events or file hashes.
osquery> SELECT name, path, pid FROM processes WHERE on_disk = 0; name = Drop_Agent path = /Users/jim/bin/dropage pid = 561
New to back-end/infra development? Just need a refresher? Here’s an intro to some common data storage options and when you might use them.
Yesterday I was working on an explanation of window functions, and I found myself googling “can you filter based on the result of a window function”. As in – can you filter the result of a window function in a WHERE or HAVING or something?
Eventually I concluded “window functions must run after WHERE and GROUP BY happen, so you can’t do it”. But this led me to a bigger question – what order do SQL queries actually run in?
Kind of a snappy headline because Julia is talking about order in terms of execution and most of the time we’re thinking about order in terms of authoring. But still, TIL!
SQL injection is a serious vulnerability, effectively allowing an attacker to run roughshod over your entire database. If you’re using Sequelize, drop everything (pun unintended) and get patched up.
As a testament for Sequelize’s commitment to security and protecting their users as fast as possible, they promptly responded and released fixes in the 3.x and 5.x branches of the library, remediating the vulnerability and providing users with an upgrade path for SQL injection prevention.
I think all ORM users have a journey from ‘there should be a way to’ to ‘this is saving me so much work’ to ‘I have to reach into the vending machine to get my change out’.
I see the value in ORMs, but I also see where Abe is coming from in this article. I think the sweet spot for an ORM is when you’re just getting started making apps and you want to minimize how many technologies you need to learn to get there. I certainly learned SQL over a slow, productive period while utilizing its features from the warm embrace of Active Record.
Stick around to the end of the article where he reveals the anti-ORM he’s working on to solve some of these problems.
RAPIDS.ai, for the uninitiated, is a data science framework that lets you execute entirely on GPUs.
Today we are happy to announce PartiQL, a SQL-compatible query language that makes it easy to efficiently query data, regardless of where or in what format it is stored. As long as your query engine supports PartiQL, you can process structured data from relational databases (both transactional and analytical), semi-structured and nested data in open data formats (such as an Amazon S3 data lake), and even schema-less data in NoSQL or document databases that allow different attributes for different rows.
OctoSQL is a SQL query engine which allows you to write standard SQL queries on data stored in multiple SQL databases, NoSQL databases and files in various formats trying to push down as much of the work as possible to the source databases, not transferring unnecessary data.
OctoSQL does that by creating an internal representation of your query and later translating parts of it into the query languages or APIs of the source databases. Whenever a datasource doesn’t support a given operation, OctoSQL will execute it in memory, so you don’t have to worry about the specifics of the underlying datasources.
If you like writing SQL, you’ll probably like OctoSQL.
After I wrote about Stein earlier today, I got to wondering about open source alternatives to Google Sheets. Coincidentally, this article popped up in my RSS reader.
EtherCalc can be self-hosted or there are hosted offerings, including one at EtherCalc.org. It looks a bit rough around the edges, but that’s often the case with open source GUIs. Maybe kick the tires and blog about your experience? We’d happily log the results here on Changelog News.
This looks like a great option for proofs of concept or when you want to take an idea to market as fast as possible. It’s also probably empowering to non-developers on the team since so many people can slice-n-dice spreadsheets better than SQL databases. You can self-host the open source version or pay for the hosted offering. I’d love to see a comparison between this and Airtable.
Computer Scientist Yaw Anokwa joins the show to tell us how Open Data Kit is enabling data collection efforts around the world. From monitoring rainforests to observing elections to tracking outbreaks, ODK has done it all. We hear its origin story, ruminate on why it’s been so successful, learn how the software works, and even answer the question, “are people really using it in space?!” All that and more…
This wraps up a pre-trained model for SQLova. Here are some examples using the ‘bridges’ dataset. 👇
Michael Malis at !!Con 2019:
Writing SQL can be hard. SQL code is a bizarre combination of yelling and relational algebra. How can we make writing SQL easier? By embedding our own programming language in our SQL queries of course! In this talk, we’ll take a look at how you use a combination of various Postgres features to build a programming language out of SQL.
EdgeDB combines the simplicity of a NoSQL database with relational model’s powerful querying, strictness, consistency, and performance.
It boasts strongly typed schemas, native GraphQL support, a rich standard library, built-in support for schema migrations, and more.
How does a database work? What format is data saved in? How are indexes formatted? When and how does a full table scan happen? Join Connor Stack on his journey to answer these questions and more…
I’m building a clone of SQLite from scratch in C in order to understand, and I’m going to document my process as I go.
I’ve learned a lot of skills over the course of my career, but no technical skill more useful than SQL. SQL stands out to me as the most valuable skill for a few reasons:
- It is valuable across different roles and disciplines
- Learning it once doesn’t really require re-learning
- You seem like a superhero. You seem extra powerful when you know it because of the amount of people that aren’t fluent
I tend to agree. I still use (and sometimes love) ORMs and database libraries while building apps, but the more I’ve learned SQL over the years, the more I appreciate it for what it is.
Craig drills into each of his 3 points above in this excellent post.
This blog post is about Badger, the key-value database that makes it all happen under the hood, housing all Dgraph data, including Raft logs.
There are many key-value store options in Go-land. Still, the Dgraph team decided to roll their own solution 18 months back. Was it a bad case of NIH? A good idea? Would they do it all over again? This article answers those questions in-depth.