janemanos

True, there are already some tools available to improve Kubernetes resource usage. Some might also use the VPA that comes with K8s. With Optimize Live we focused on the developer experience and precision of our recommendations.

Optimize Live can look at all historical data and trends and uses our machine learning algorithm to recommend improvements. From an engineering perspective, you don't need to write YAML files, write load test or make your way through complex configurations. The recommendations for more optimal configurations comes directly as YAML file which you can either deploy manually after checking or automatically and put optimization on autopilot once you feel comfortable with the tool.

My opinion is for sure biased but at the moment, we think we have the simplest solution to the problem of over-provisioning, CPU throttling or OOM issues.

Thanks!

Would say it comes down to what risk you are willing to take.

If you use a logo without permission especially from a larger corp, you might run into legal issues or maybe even jeopardize a deal that is in the making with your company.

Some public record clearly stating that a company X is using you can help to migitate the risk (public Job posting, article, webinar, etc.)

And of course always take down the logo if someone from the company is complaining. The very best is always to get permission from the companies marketing, business, legal or sometimes even hiring department, depending on the market you are in. Would recommend to go for case studies highlighting them and their solution and then get the logo that way.

Hope I could help a bit...

Thanks :) Jan from ArangoDB here

You can see the exact pricing for the deployment configuration you desire within Oasis when you create a deployment. In general, the actual price for your deployment depends on the cloud provider, amount of main memory & storage you selected. The pricing is usage based, so if you only need a deployment for one hour, you only pay for that hour. Hope this helps a bit at least.

Here is the repo on Github https://github.com/arangoml/arangopipe

Supporting full distributed ACID transactions is the holy grail for databases, especially if you want them with minimal performance impact. For single instance settings we guarantee full ACID semantics and in a cluster setting ArangoDB supports atomic operations. Getting full distributed transactions working and minimizing their performance impact on writes is something we are still investigating. The new streaming transactions API in v3.5 brings also improvements to handling of transactions in a clsuter but are not distribuzed transactions.

For more details please see our docs https://www.arangodb.com/docs/stable/transactions-transactio...

Congrats to the whole team!

I guess more and more people are turning towards search engines directly integrated into databases, like ArangoSearch of ArangoDB to combine search with other needs https://www.arangodb.com/why-arangodb/full-text-search-engin...

Will be interesting to see how other open source projects like ArangoDB (Apache2), Timescale (Apache 2) or Scylla (AGPL/Apache2) will react.

Think we have to be a bit more precise here. ArangoDB supports documents, key/value, and graph. It is not really optimized for large timeseries use cases which might need windowing or other features. Influx or Timescale might provide better characteristics here. However, for the supported data models we found a way to combine them quite efficiently.

Many search engines access data stored in JSON format. Hence integrating a search engine like ArangoSearch as an additional layer on top of the existing data models is no magic but makes a lot of sense. Allowing to combine models with search is then rather an obvious task for us.

you might find this interesting: https://www.innoplexus.com/blog/products-powered-by-arangodb...

Jan from ArangoDB here. Can't disclose anything yet but feel free to join the webinar of our co-founder Claudius. He will share details about our future plans in only 2 weeks https://www.arangodb.com/arangodb-events/why-native-multi-mo...

Congrats, guys!

Think CosmosDB just is not too appealing with it's layered multi-model approach compared to ArangoDBs native way to support multiple data models in one db.

the cool thing about Arango is that you can use all data models also in a cluster setting and combine the models as you need. A pretty nice and helpful community around the project as well.

Sounds kind of "old" tech to have different layers for supporting different data models. Like the native multi-model approach of ArangoDB much better.

Their aggregation framework is pretty neat and the database also has full graph capabilities. Heck, I can even combine joins and graph traversal in the same query.

The simplest explanation is that ArangoDB uses JSON as dataformat to the outside world. JSON doesn't support these types like arbitrary exact decimal, or timestamps. Despite ArangoDB using VelocyPack internally, which is capabable of much more than JSON, a user will import JSON and get JSON back.

You can of course use datetime https://docs.arangodb.com/3.3/AQL/Functions/Date.html and decimals with a precision of 10E38 in ArangoDB but it is not as precise as in a relational database. If we want to be as precise as a relational DB, then we would have to say goodbye to JSON

This is on the list of more than one teammate here at ArangoDB. But also not trivial to implement.

ArangoDB also has a first tool to listen to changes in the database and execute actions or queries. It is limited to a single node. Question is how scalable all of these tools are https://www.arangodb.com/2017/03/arangochair-tool-listening-...

Have you ever had a look into analyzing processes with a graph database like e.g. ArangoDB. Wonder if that would make sense for your needs. You can traverse along the processes, find patterns or use distributed graph processing with Pregel analyze from different angels. edit:typo

Don't forget native multi-model databases like ArangoDB

What concernes me is that the article is strongly biased in the sense, that modern developments of non-relational databases just get ignored while ranting on their state from a few years ago. Schemaless databases do support full ACID transactions (MongoDB, ArangoDB), with some you can also enforce a schema and not everybody loves SQL. So having competition even on the query language-side, can only improve the status quo.

Yes, thinking about your data model will for sure increase your understanding of what you are actually doing... and every professional developer is doing this as well when choosing a non-relational database. Anythings else would be stupid.

For me the article rather shows that the modern developments in non-relational databases do affect vendors on the relational side of the spectrum. Otherwise, it would not make sense to invest so much time in writing such a long article.

Kind of a weekend read but definitely worth my time

Well, not that easy for a larger project to switch to another platform. I work for ArangoDB and as silly as it sounds but leaving the street and investor cred of our Github Stars behind is not really an option, kind of a lock-in is also there on Github

The stallement of the further development of autonomous cars seems rather a marketing thing on Toyota and Uber side than actual analysis of what happens. Still think that self-driving cars are already much safer than a human behind the wheel. As Musk said, it is not difficult to get to 99.9%, the important things is to get to 99.99999% of accuracy and reliability

Hi Jan from ArangoDB here.

2-digit TB of graph data is for sure a serious graph :) Depending on what you actually want to analyze and how the graph is structured, you can either use our Pregel integration for high-level analytics of the data set or use SmartGraphs to shard the data to a cluster and perform in-depth traversals, pattern matching and such stuff. SmartGraphs is an Enterprise feature but free for evaluation and testing. Please note that the suitability of SmartGraphs depends on the structure of the graph itself (e.g. do you have or can identify communities to shard by efficiently)

We created a series of tutorials which guide you through such a process https://www.arangodb.com/pregel-community-detection/ (next step always at the end of each tutorial). You can choose between two storage engines. Think RocksDB is the better choice in your case, as everything is persisted to disk (data/indexes) and you can configure how much main memory should be used, so you can configure the trade-off between performance and main memory yourself. If you have fast SSDs it's even better, as RocksDB is optimized for that.

Well, the cost for GDPR won't be that high, if the EU would have thought this through. Talked to a few of the GDPR "Consultants" and as soon as people have some more in-depth questions how A or B can be handled, you just get a surprised look. I'm all for better protecting my information but if you introduce these regulations you, as the regulator, also have to have answers to basic questions.

It will cost companies so much money and time to be compliant with GDPR. Maybe even become a neck-breaker for some young startups

We just published an Update to the Benchmark, please find it here: https://news.ycombinator.com/item?id=16473117

We just published an Update to the Benchmark including PGtune, please find it here: https://news.ycombinator.com/item?id=16473117