Memgraph VS Plausible Analytics

Memgraph | Staff C++ Database Engineer | REMOTE (Central/Western Europe, LatAm, or North America) https://memgraph.com/

Memgraph is a Seed stage, open source graph database vendor. Graph DBs are a great solution for GenAI, logistics, cybersecurity and fintech so we are looking to grow aggressively this year.

We're looking for a staff-level engineer to set technical direction, mentor junior team members, and solve some very difficult problems.

Either DM me (the hiring manager) or apply here: https://join.com/companies/memgraph/10684850-staff-software-...

It's not possible to escape tradeoffs. To deal with tradeoffs, focus is important. API to tradeoffs is also important.

I bet somebody will raise a similar question in a few years time when the list under https://db-engines.com/en/ranking/graph+dbms will be bigger.

DISCLAIMER: Coming from https://github.com/memgraph/memgraph

Albeit the significant engineering endeavor, the larger-than-memory architecture is a super valuable asset to Memgraph users since it allows them to store large amounts of data cheaply on disk without sacrificing the performance of in-memory computation. We are actively working on resolving issues introduced with the new storage mode, so feel free to ask, open an issue, or pull a request. We will be more than happy to help. Until next time 🫡

NoSQL databases are non-relational databases with flexible schema designed for high performance at a massive scale. Unlike traditional relational databases, which use tables and predefined schemas, NoSQL databases use a variety of data models. There are 4 main types of NoSQL databases - document, graph, key-value, and column-oriented databases. NoSQL databases generally are well-suited for unstructured data, large-scale applications, and agile development processes. The most popular examples of NoSQL databases are MongoDB (document), Memgraph (graph), Redis (key-value store) and Apache HBase (column-oriented).

Whether it's about identifying similar user profiles in a social network, detecting similar patterns in a communication network, or classifying nodes in a semantic network, cosine similarity contributes valuable insights. Combined with a powerful graph database system, such as Memgraph, it gives a better understanding of complex networks. Memgraph is an open-source in-memory graph database built to handle real-time use cases at an enterprise scale. Memgraph supports strongly-consistent ACID transactions and uses the standardized Cypher query language for structuring, manipulating, and exploring data.

It should be noted this article is on the blog of a project which advertises itself as open source, under a BSL license that puts limitations on distribution and use.

At the moment, benchgraph is a project under Memgraph repository (previously Mgbench). It consists of Python scripts and a C++ client. Python scripts are used to manage the benchmark execution by preparing the workload, configurations, and so on, while the C++ client actually executes the benchmark.

These five steps will result in something similar to this simplified version of demo.py example:

Take a look at this blog post about choosing the optimal index. It focuses on Memgraph graph database but it offers a theoretical background that is not vendor related.

In this tutorial, we will utilize betweenness centrality for identifying essential proteins. For this task, we are using Memgraph, a graph analytics platform, which can perform complex graph analysis on all sorts of networks. Even though we will use betweenness centrality, other graph algorithms can also be applied to the protein-protein interaction network, such as other centrality measures or the PageRank algorithm.

I think a single Google Analytics alternative is pretty hard to pick considering that GA can be used to very much varying extents.

For simple and "detailed enough" insights, I enjoyed using Plausible (https://plausible.io/) in the past.

For more in depth analytics that give you a detailed view into your own product, PostHog.com seems to be by far the best and most popular option out there.

I could do the same exercise with Google Analytics and Google Tag Manager, but luckily I don't need to, since Plausible already did. A piece of advice, rip out Google Analytics and use Plausible instead. It first of all doesn't destroy your website, and secondly it doesn't violate the GDPR - So you can embed it on your site without having to warn your visitors about that they're being spied on by Google.

Also, currently we are using https://plausible.io/ for analytics. No other bugs.

I just swapped out Google Analytics with Plausible for AINIRO.IO. It’s only been a week, but so far I am super jazzed about it. First of all, Plausible doesn’t use cookies, so I can completely drop all cookie disclaimers and popups I had because of GDPR. Second of all, the site scores significantly better on load time. This results in a 10x better user experience for my website visitors, while making sure the website is still 100% conforming to GDPR laws.

No clue what you mean, browser cache might even clear itself without you doing anything manually. This thing makes no sense.

Nowhere ever did it say Tech Demo anywhere, not in the HN headline, not on the page itself. No, thanks. And even as a tech demo, there is nothing impressive going in. It is stores shit to local storage, I guess. Lol, I just looked this up, and it was in Firefox on 2009 already? WHAT? https://developer.mozilla.org/en-US/docs/Web/API/Window/loca... I never used it myself directly, but I remember reading about some API that kind of is the new version of cookies that can store more and better and I think that is it. 2009, I would swear what I think about was newer, maybe I am mixing something up, maybe not.

It has unnecessarily tracking from the comment above, not sure if it even sends all your notes to https://plausible.io, and I do not care. For me, this fails as a tech demo or whatever the fuck It's supposed to be. Sorry to not get all excited about everything posted here. In 2009 it for sure would ;)

If you already use Posthog, Web Analytics has been in Public Beta for quite some time.[1]

If I remember correctly, CloudFlare Analytics does not need you to register your domain with them. I personally feel keeping domain registration coupled with your DNS provider is not a good idea.

Plausible[2] has an Open Source self-hostable version but is not so updated in sync with their SaaS version.

Umami[3] is another simple, clean one. And, of course, as many have suggested, Matomo is the other well-established one. If you want to avoid maintaining a hosting routine, a lot do the hosting out of the box these days. PikaPods[4] was good when I tried and played around for a while.

1. https://posthog.com/docs/web-analytics

2. https://github.com/plausible/analytics

3. https://umami.is

4. https://www.pikapods.com

Plausible - Open Source Alternative to Google Analytics

There are many good, lightweight, and open-source alternatives to Google Analytics, such as Plausible, Matomo, Fathom, Simple Analytics, and so on. Many of these options are open-source, and can be self-hosted.

You log the IP address, referrer, user agent and the requested page URL but you don't set a unique cookie to identify the user.

This still gets you plenty of actionable analytics information: where geographically people are located (via GeoIP), what pages are most popular, what platforms (including desktop vs mobile) people are using.

I've been using https://plausible.io for analytics on a bunch of my sites for a couple of years now and I honestly don't miss the extra level of detail I got from cookie-based analytics I've used in the past.