ifcologne

This has the potential to accelerate the blocking of spam and troll accounts.

Is anyone already implementing such a service?

I often hear the argument that one should only use the standard or in the cloud, the (OpenSource) tool specific features to be able to move anywhere else anytime.

No use of AWS specifics which would make developers live easier but doesn’t exist in Azure. SQL Standard instead of effective new datatypes or procedures that are vendor specific.

My favorite quote of the article:

„Data has gravity“. Moving data can be both time-consuming and costly.

This is a major lock-in that is often ignored.

Ingo from ArangoDB here:

If you need to scale-out, the ArangoDB packages are more affordable then MongoDB Atlas, as you don't need to spin-up a whole 3 node replica-set to add another shard to your cluster. The smaller instances are cheaper in Atlas, here you benefit from the established cloud service, which can negotiate better conditions with the large cloud providers. However, we will pass on lower cloud costs to customers, so there is hope that we will move closer over time. But, I don't see ArangoDB in direct competition with smaller, pure document-use cases. Most users need the multi-model capabilities and use graphs in combination with document operations.

Yes. Now I need to refine my backlog. A lot of great ideas I didn't thought about yet.

A lot of users don't care and are used to these tactics. Is there a chance that this will change in the future? I hope so.

What I miss in the conclusion: Multi-model databases

More and more products support multiple data models today.

This reduces the number of technologies in your tech stack and allows to combine different access patterns without the need to duplicate and sync data between systems.

Good explanation of TF-IDF. Now I can verify if my colleagues have implemented it in the same way.

Okay, Stephen O’Grady - here’s the obvious one you’ve asked for:

CSS is not a programming language. ;-)

Despite that, the list is quite complete and feels reasonable. Did you try to research how languages are used in certain use cases? Which languages compete in a certain domain?

Imagine you would go to your preferred online marketplace and search for a generic product.

You get 1000+ results.

So you filter by avg.star-rating > 4.0

Still 500+ results.

Those with just one 5 star rating in front of the one with 300 reviews and a 4.8 avg. Annoying.

What I really want:

I would like to filter for products that have at least 5 (relatively long) reviews, an average rating of 4.0 and at least 2 of these review comments mentioning the use case for which I would like to use this product. Maybe I just want the verified purchases to be counted or the reviews of friends and friends of friends...

Using a native multi-model approach you can do both. Simply retrieve all category X products ranked by product rating, limit 50/page or perform advanced lookups - without having to synchronize data from a document or relational model with an additional graph or search engine.

Combining full text search with scorers, graph traversals and/or join operations you could do an ad-hoc query in AQL to get the most relevant products & reviews with a single query.

Multi-model provides choice. In data modeling and querying.

The art is to combine all data models using one query language without duplicating data.

Yes, we had cluster stability issues 1.5 years ago. That has changed, cluster stability and performance has the top priority and we invest a lot to improve the developer and devops experience with every release. Now, e.g. with K8s deployments or the arangodb starter, it's much easier to run and maintain clusters. Hope you find the time to give it a second try.

Pricing for smaller workloads is better on MongoDB Atlas right now. The DocumentDB performance pays of for super large collections and really high read/write workloads.

Search is a new feature that could be used without limitations, in every edition. It’s really powerful if you combine a full-text search with a traversal or document join.

I‘m using Apple devices since 12+ years and never regret that I switched. The Apple support is the biggest plus. All the other 4 reasons are absolutely valid and keep me in the eco-system. It comes with a high price tag. But as I get the latest updates for iOS devices I have no need to change my iPhone every 2 years - I‘m fine with my iPhone 6. Perhaps until autumn this year...

I rate your idea zero stars.

You might want to but you are forced to provide a one star rating instead. :)

Performance tests - especially those of databases - are a very complex and resource-consuming venture. And because each use case is different, the benchmark published somewhere does not fit your specific problem and the available environment/budget.

Unfortunately, there is no independent organization that believes in this and defines scenarios that are tested in different environments.

They should be blogging about use cases and customer successes, not benchmarks.

They do, just recently the cases of AskBlue (Location aware recommendations) and Thomson Reuters (Fast & Secure Single-View of Everything)

https://www.arangodb.com/why-arangodb/case-studies/

I am very interested in Graph-Cases and appreciate the support of Neo4J for projects like the Panama- or Paradise Papers that show how connected graphs help to understand former hidden relationships. Graphs are very powerful and a great addition to relational or document approaches.

(full disclosure: I worked for ArangoDB 2 years ago.) And, I've used Neo successfully for a fraud detection PoC recently...

So does the multi-model database ArangoDB. https://docs.arangodb.com/3.2/AQL/Examples/Join.html

And some NoSQL databases speak SQL as well - without being relational.

I like the JSON support in PostgreSQL a lot. Very easy to deal with unstructured JSON data while still using common attributes in a relational format. But there are more cases that one might think about - as a relational guy - that benefit from graph databases, document stores or optimized time-series databases.

My 3 yo borrows my iPhone when we ride home from kindergarden and I don't want that he fells asleep. So he watches an episode of Fireman Sam on Amazon Prime or plays a game. He unlocks the phone with his "magic finger" and after 20 min I get my phone back.

It would be so fantastic if he could just start HIS apps and would access a restricted Prime account. My 6 yo is the same and since he was 2 1/2 I switched by iPhone twice. So I don't see the case that it's not important as they will get their own ones when they are 8 or so - that's 5 generations of iPhones.

Thanks for this lesson in history (follow the links to more details) and a story about the current system in Korea.

It is hard to imagine growing up in a totally isolated country and not knowing anything about the outside world.

Not for all problems but for some technical ones I use lovely curated awesome lists.

https://github.com/sindresorhus/awesome is a good starting point.

Nice tool to build graphs. Except of creating edges between notes it also works on touch devices.

Great to have exports and png support as well. Bookmarked.

Congrats, ArangoDB team!

Reading through the release notes and related blog posts lead to several wow's and nods.

Especially the satellite collection feature that allows local joins in cluster mode sounds promising. Can't wait to learn from successful real world implementations.

Hope to find some time to get used to all those new features announced today.

Lot's of interesting data and some findings I didn't expected. Thanks.

What I have missed in this paper is the impact of customer reviews (a 4.5 ranking has a higher uplift potential than a 5.0 star ranking - according to some studies). And the number of reviews has impact as well. Not enough studies around for a meta analysis?

Rootclaim wants to calculate if a story is true by taking all the evidence, consider its reliability, put it to the probabilistic test and come up with the most likely conclusion.

However, people may sometimes have “context-based rationality”… If you are clearly and emotionally on one side of an issue, I don’t think we will convince you otherwise.

So true.

How much effort do I have to invest to get a glimpse on the new graph viewer?

Do I have to deploy a new ArangoDB 3.1 and generate some test data myself or is there a demo available for a first impression?

This is big news.

Great move and necessary to compete in the fast growing market of data-center automation. I hope that DC/OS gets as much attention in the open-source community as Kubernetes already does.

https://www.arangodb.com

A database that you can use as a JSON document store or a graph database - or even both data models combined - within a single query.

Why it's awesome?

I can use one technology for so many different use cases, I'm not limited to one data model and can use a single query language that supports graph traversals and document JOINS.

It's designed to support modern microservice architectures and orchestration - e.g. via Mesosphere DCOS.

Using a novel index, which combines hashes with linked-list, it is possible to gain the same complexity O(n) when traversing the whole graph.

Index-free adjacency is an implementation detail - with drawbacks:

If you store the vertices at each node as list of direct pointers, then traversing all neighbors has complexity O(k), if a vertex has k edges. Note that this is the best possible complexity because O(k) is the size of the answer. Deleting a single edge also has the same complexity of O(k) (assuming a doubly linked list), which is much worse.

Furthermore, usually one will want to be able to traverse edges in both directions, which makes it necessary to store direct pointers on both vertices that are incident with an edge. A consequence of this is that deleting a supernode is even worse: To remove all incident edges one has to visit every adjacent vertex – and perform a potentially expensive removal operation for each of them.

In general, a graph database is “a database that uses graph structures for semantic queries with nodes, edges and properties to represent and store data” (Wikipedia) – independent of the way the data is stored internally.

A worth to read article by [Mike Malone](https://medium.com/@betable/tifu-by-using-math-random-f1c308...) explains the problem with Math.random() in more detail.

Quoting Donald Knuth / The Art of Computer Programming:

“Many random number generators in use today are not very good. There is a tendency for people to avoid learning anything about such subroutines; quite often we find that some old method that is comparatively unsatisfactory has blindly been passed down from one programmer to another, and today’s users have no understanding of its limitations.”

ArangoDB GmbH | Cologne, Germany | ONSITE

* Senior Software Developer C/C++

* Java Developer JEE, SpringData

ArangoDB, Cologne/Germany is seeking experienced software developers to join our database development team. ArangoDB is a multi-purpose, open-source database with flexible data models for documents, graphs, and key-values.

https://www.arangodb.com/jobs/

Contact: jobs@arangodb.com