quix
logica
quix | logica | |
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1 | 19 | |
267 | 1,689 | |
0.0% | - | |
6.5 | 9.0 | |
26 days ago | 3 days ago | |
TypeScript | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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quix
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Aerospike Data Browser
Aerospike Data Browser is basically a stack that consists of Quix, Presto, and the Aerospike Connector for Presto, and is dockerized. Figure 1 depicts an under the hood view. The Quix UI provides a DB Explorer and a SQL editor, in addition to a notebook manager for managing your notebooks. Presto exposes a JDBC interface to Quix and uses the Aerospike Connector to translate SQL queries into API calls to the DB. Building a stack with the aforementioned components for a desktop installation is not trivial by any means. Presto can scale to 100’s of nodes for a large scale deployment, but we wanted to limit the data browser to a single Presto instance that would run both the coordinator and worker in the developer's desktop environment. Our initial size of the Presto docker image was over 2GB, which was not acceptable. Hence, we stripped out all but the Aerospike connector from the plugin directory. Similarly, we had to downsize the Quix connector. Finally, we got the compressed docker image size under 1GB. We also made a design decision to default to schema inference so that a user that does not know the schema apriori is not left out.
logica
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Prolog language for PostgreSQL proof of concept
If you're interested in this I would also recommend you check out Logica[0], which is a datalog-like language that is explicitly made to compile to SQL queries.
0: https://logica.dev/
- Logica
- New welcome page for Logica language
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Introduction to Datalog
> I guess the intention is to be better than SQL but then I was left with "under which circumstances?"
Excellent question.
Two of the most common use cases for databases are "transactional processing" (manipulating small numbers of rows in real time) and "analytical processing" (querying enormous numbers of rows, typically in a read-only fashion).
SQL is generally fine for transactional workloads.
But analytical queries sometimes involve multi-page queries, with lots of JOINs and CTEs. And these queries are often automatically generated.
And once you start writing actual multi-page "programs" in SQL, you may decide that it's a fairly clunky and miserable programming language. What Datalog typically buys you is a way to cleanly decompose large queries into "subroutines." And it offers a simpler syntax for many kinds of complex JOINs.
Unfortunately, there isn't really a standard dialect of Datalog, or even a particular dialect with mainstream traction. So choosing Datalog is a bit of a tradeoff: does it buy you enough, for your use case, that it's worth being a bit outside the mainstream? Maybe! But I'd love to see something like Logica gain more traction: https://logica.dev/
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Mangle, a programming language for deductive database programming
Interesting; a Google engineer previously published a Datalog variant for BigQuery: https://logica.dev/
This new language seems similar to differential-Datalog (which is sadly in maintenance mode): https://news.ycombinator.com/item?id=33521561
- Show HN: PRQL 0.2 – Releasing a better SQL
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Show HN: PRQL – A Proposal for a Better SQL
Looks pretty cool. I'd be interested if the README had a comparison with Google's Logica (https://github.com/EvgSkv/logica)
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PathQuery, Google's Graph Query Language
Oh wow that is neat!
And yes, this kind of thing is why datalog is a lot more amenable to fast query plans & runtimes than prolog. This part is especially cool: https://github.com/EvgSkv/logica/blob/main/compiler/dialects...
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Thought about Logica: Google new programming language that compiles to SQL ?
Google new programming Language that compiles to SQL (Support BigQuery and Postgres) feels very exciting. Blog: https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html Github: https://github.com/EvgSkv/logica
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Google Logica Aims To Make SQL Queries More Reusable and Readable
Going to be? It already is. In fact, one thing the article misses is right there at the bottom of the project page:
What are some alternatives?
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
scryer-prolog - A modern Prolog implementation written mostly in Rust.
aerospike-data-browser - Data Browser for AerospikeDB
ungoogled-chromium-archlinux - Arch Linux packaging for ungoogled-chromium
malloy - Malloy is an experimental language for describing data relationships and transformations.
prql - PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
differential-datalog - DDlog is a programming language for incremental computation. It is well suited for writing programs that continuously update their output in response to input changes. A DDlog programmer does not write incremental algorithms; instead they specify the desired input-output mapping in a declarative manner.
materialize - The data warehouse for operational workloads.
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
rfcs - RFCs for major changes to EdgeDB
tresql - Shorthand SQL/JDBC wrapper language, providing nested results as JSON and more