ArangoDB VS H2

ArangoDB

... or working in an environment or on a problem for which functional patterns apply.

Suppose you are writing a "CRUD" app that writes to a relational database, how do you apply functional programming to that? The whole point of an application like that is that it makes side effects.

In some cases you can break those problems down into functional pieces. Consider Python drivers for a product like

https://www.arangodb.com/

One major problem is that you want drivers that work synchronously and asynchronously, the structure of the average api call is something like

   def query(parameters):

First, you need to choose a specific graph database platform to work with, such as Neo4j, OrientDB, JanusGraph, Arangodb or Amazon Neptune. Once you have selected a platform, you can then start working with graph data using the platform's query language.

Some databases like ArangoDB (https://www.arangodb.com/) allow you to use Javascript instead of SQL.

However, using a type-unsafe, turing-complete language introduces type unsafety and turing-complete problems to the query layer; the usual problems we know and love, such as infinite loops, runtime type errors, exceptions, and the like.

Personally, I'm looking forward to a WASM runtime for databases -- so we can run webassembly on the database. This COULD be carefully designed to be statically checked and, possibly, make it really hard to write runaway loops.

When it comes to graphdb's, my favorite is still ArangoDB, definitely worth checking out if you are looking for alternatives.

https://www.arangodb.com

Personally my favorite db for pet projects is

https://www.arangodb.com/

I think you hear very little about it because ADB users see it as a "secret weapon" to crush their competitors with. I've done large ontology work (MESH and other health ontologies) and IoT work (keep several years of sensor readings for sensors in my house) and workflow systems (select interesting HN articles or jobs I want to apply to) and it has never let me down. I haven't run a real instance serving customers in the cloud though.

For the last few years every eng manager I have worked with has been a fan of

https://www.postgresql.org/

In the early 2000s I thought it overpromised and underdelivered and called it CrashGreSlow but after MySQL got bought by Oracle the pgsql team has worked hard to improve it I think it is great today. It supports all kinds of advanced features such as stored procs, full-text search, JSON equivalent fields, etc.

Hi! I recently came across ArangoDb and used in some POCs, but I really want to know if someone here already used it in a Real World environment or even if chose to not use in a production environment. So... have you ever used ArangoDb? Why? Why not?

For mutual friends, we can build a social graph for every user. Each node in the graph will represent a user and a directional edge will represent followers and followees. After that, we can traverse the followers of a user to find and suggest a mutual friend. This would require a graph database such as Neo4j and ArangoDB.

ArangoDB

This a NOSQL database built for high availability and high scalability, a perfect fit for implementing persistence in microservices. ArangoDB is an open source native multi-model database that supports graph, document and key-value data models allowing users to freely combine all data models in a single query. Dive deeper into this database and its features here.

The URL should point to a particular comment, but HN removes fragments: https://github.com/h2database/h2database/issues/3686#issueco...

This sounds very much like the idiocy of "infosec" lunkheads who know nothing about what they're "fixing" but if an automated system tells them a CVE exists, they've absolutely got to have it "patched". They don't look into what the claims of the CVE are, or whether their specific use case is vulnerable. They don't know, they don't care, they're not even programmers. All they know is a box needs ticking.

A similar thing happened with h2database - a "security researcher" found that if you do something you're told not to do, then bad things happen.. but they demanded and got a CVE allocated anyway. Anyone who looks at it realises it's bullshit, but the mere existence of a CVE is all that matters to these idiots.

What the h2database developer said about it: https://github.com/h2database/h2database/issues/3686#issueco...

> I struggle to understand why I should feel the slightest shred of sympathy for "major corporations" that are using a volunteer-developed open-source project. Feel free to get your corporation to pay someone to deal with this, or pay for a similar commercial library.

> ...than it would be to learn the exact syntax and quirks and possibly bugs of someone else's implementation...

Yup. Also, having deep knowledge of the language is required.

SQLite's grammar is neat. Creating a compatible parser would make a fun project. Here's a pretty good example: https://github.com/bkiers/sqlite-parser (Actual ANTLR 4 grammar: https://github.com/bkiers/sqlite-parser/blob/master/src/main... )

Postgres, which tries to be compliant with the latest standards, however...

SQL-2016 is a beast. Not to mention all the dialects.

I'm updating my personal (soon to be FOSS) grammar from ANTLR 3 LL(k) to ANTLR 4 ALL().

I've long had a working knowledge of SQL-92, with some SQL-1999 (eg common table expressions).

But the new structures and extensions are a bit overwhelming.

Fortunately, ANTLR project has ~dozen FOSS grammars to learn from. https://github.com/antlr/grammars-v4/tree/master/sql

They mostly mechanically translate BNFs to LL(k) with some ALL(). Meaning few take advantage of left-recursion. https://github.com/antlr/antlr4/blob/master/doc/left-recursi...

Honestly, I struggled to understand these grammars. Plus, not being conversant with the SQL-2016 was a huge impediment. Just finding a succinct corbis of test cases was a huge hurdle for me.

Fortunately, the H2 Database project is a great resource. https://github.com/h2database/h2database/tree/master/h2/src/...

Now for the exciting conclusion...

My ANTLR grammar which passes all of H2's tests looks nothing like any of the official or product specific BNFs.

Further, I found discrepancy between the product specific BNFs and their implementations.

So a lot of trial & error is required for a "real world" parser. Which would explain why the professional SQL parsing tools charge money.

I still think creating a parser for SQLite is a great project.

H2 - Free, Embedded & Open source

H2 2.1

H2 for mocking relational database connections

It's open-source and written in Java, so you can even create custom procedures and register them straight in your application!

Firstly, let's set up a basic Spring Boot application. We can use the Spring Initializr with Spring Data JPA, H2 Database, Lombok added. H2 Database will provide us with a simple database, and Spring Data JPA will allow us to easily interact with it using Hibernate. Lombok will make it easier to write concise and readable classes.

Sorting chunks by similarity: commonly used tools don't do that. Most archive tools only sort by file type.

I wrote a tool that chunks the data (into variable-sized blocks, to re-sync if there are multiple files that have different length prefixes, but that's another story), and then sorts the chunks by LSH (locality sensitive hash). LSH is used by search engines to detect similar text. It can compress directories that contain multiple version of e.g. source code very well (e.g. trunk, branches). https://github.com/h2database/h2database/blob/master/h2/src/...

I discussed this approach with a researcher in this area in January 2020. AFAIK there is active research in this area, specially to compress DNA sequences. But he also wasn't aware of papers or research in this area for general-purpose data compression.

So, I think this area is largely uncharted. I would be interested (as a hobby side project) to help, if somebody is interested.