Apache Calcite VS sqlitebrowser

> Make diff work on more than just SQLite.

Another way of doing this that I've been wanting to do for a while is to implement the DIFF operator in Apache Calcite[0]. Using Calcite, DIFF could be implemented as rewrite rules to generate the appropriate SQL to be directly executed against the database or the DIFF operator can be implemented outside of the database (which the original paper shows is more efficient).

[0] https://calcite.apache.org/

Yes, planetiler rocks and the memory mapped collections enabled us to remove our dependency to rocksdb.

From my perspective, planetiler started as an effort to generate vector tiles from the OpenMapTile schema as fast as possible (pbf -> mvt). By contrast, Baremaps started as an effort to create a new schema and style from the ground up. In this regard, having a database (pbf -> db <- mvt) enables to live reload changes made in the configuration files. The database has a cost, but also comes with additional advantages (updates, dynamic data, generation of tiles at zoom levels 16+, etc.).

That being said, I think the two projects overlap and I hope we will find opportunities to collaborate in the future. For instance, whereas PostgreSQL is still required in Baremaps, I recently ported a lot of the ST_ function of Postgis to Apache Calcite with the intent to execute SQL on fast memory mapped collection.

https://github.com/apache/calcite/blob/main/core/src/main/ja...

A planet wide import in Postgis currently takes about 4 hours with the COPY API (easy to parallelize) followed by about 12 hours of simplification in Postgis (not easy to parallelize). I will try to publish a detailed benchmark in the future.

Use a SQL Parser like sqlglot or Apache Calcite to compile user's query into an AST.

The SQL Federation engine contains processes such as SQL Parser, SQL Binder, SQL Optimizer, Data Fetcher and Operator Calculator, suitable for dealing with co-related queries and subqueries cross multiple database instances. At the underlying layer, it uses Calcite to implement RBO (Rule Based Optimizer) and CBO (Cost Based Optimizer) based on relational algebra, and query the results through the optimal execution plan.

Awesome to see work in the DB wire compatible space. On the MySQL side, there was MySQL Proxy (https://github.com/mysql/mysql-proxy), which was scriptable with Lua, with which you could create your own MySQL wire compatible connections. Unfortunately it appears to have been abandoned by Oracle and IIRC doesn't work with 5.7 and beyond. I used it in the past to hack together a MySQL wire adapter for Interana (https://scuba.io/).

I guess these days the best approach for connecting arbitrary data sources to existing drivers, at least for OLAP, is Apache Calcite (https://calcite.apache.org/). Unfortunately that feels a little more involved.

For anyone interested, Apache Calcite[0] is an open source data management framework which seems to do many of the same things that Hydra claims to do, but taking a different approach. Operating as a Java library, Calcite contains "adapters" to many different data sources from existing JDBC connectors to Elasticsearch to Cassandra. All of these different data sources can be joined together as desired. Calcite also has it's own optimizer which is able to push down relevant parts of the query to the different data sources. However, you get full SQL on data sources which don't support it, with Calcite executing the remaining bits itself.

Unfortunately, I would not be too surprised if Calcite was found to be less performance-optimized than Hydra. That said, there are users of Calcite at Google, Uber, Spotify, and others who have made great use of various parts of the framework.

[0] https://calcite.apache.org/

Abstraction Layer - You can use something like Calcite to abstract out your data storage. https://calcite.apache.org/

We have a spread of different GitHub Actions based workflows that do stuff whenever a PR is proposed or merged:

https://github.com/sqlitebrowser/sqlitebrowser/tree/master/....

Most of those are oriented around building packages for various OS's (Linux, macOS, Windows) so people can try the latest code.

While there are some tests, they're more like extremely basic sanity tests and don't rely on Docker.

Those tests rely on whichever version of SQLite was downloaded and compiled into the GUI (as per above code snippet).

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That being said, that's for the client side GUI application. There's a server side of things too (https://github.com/sqlitebrowser/dbhub.io -> dbhub.io) that does use docker for it's automated tests:

https://github.com/sqlitebrowser/dbhub.io/tree/master/.githu...

Those are integration tests though (eg "make sure we didn't bust communication with our cli", "make sure our go library still works 100% with the server"), and a reasonably decent set of End to End (E2E) tests of the web interface using Cypress.

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Does that help? :)

Do you know about SQLite DB Browser ? It's a multi platform application that would perfectly fit your use case :).

https://sqlitebrowser.org/

Someone gave you a sqlite database. You probably started to think to install a program like sqlitebrowser, but only to view and read the data. Don't bother, you can use this extension instead.

Try https://sqlitebrowser.org/ it’s great for local use and training purposes

You can see how the db file looks for the app using https://sqlitebrowser.org/

If you want to fiddle with SQLite and don't need all the power herein, I recommend DB Browser for SQLite.

https://sqlitebrowser.org/

Hello y'all. This is my first post here. I'm learning SQL with the Northwind database. When I run a "big" query, like "SELECT * FROM Customers" the application crashes. I noticed this only happens when I run a general query, for example, if I run something more specific (and, by the hand "smaller") it doesn't happen. So, I thought it could be related to the size of the query. But I'm a total beginner so idk. It doesn't happen every time I try to use it, but still, this is frustrating. If there's no solution, what other SQL application can I use to keep learning? I found something on GitHub but this is for an older macOS version.