octix

To me that would be a red flag. If it's difficult to setup within your tests then it's difficult within your code and/or too much magic is happening.

Thanks for sharing. "adding indexes to large collections" - how many records are we talking here?

Thanks.

From personal experience.

1) MongoDB allows me to be more agile. I don't have to deal with database migrations (No locks when adding new column for example), which allows deployments at any time.

2) Indexed arrays. Allows to add "tags" to any entity which are useful in production (A/B testing, force specific behavior).

3) Easier to manage. I don't need an expensive PostgreSQL consultant to setup and hope for the best.

Your mileage can vary.

If you can't cook it, it doesn't mean it's not tasty...

You don't have to use them, but it's really great for getting started. You can fine tune these by excluding pieces you don't need to auto configured.

http://docs.spring.io/spring-boot/docs/current/reference/htm...

Thanks for posting. I'm waiting for a x230t and was thinking about trying Centos 7 and FreeBSD too at some point.

I personally hate it, but my wife loves it. We don't argue and I just don't use it.

That said, you just cannot compare an OS running natively (is that a word?) with a VM.

Can you elaborate please? Linux running inside a VM?

Does FreeBSD play nice with resolutions higher than 1080? I mean, I know linux still has issues and I always thought *BSD a re bit behind when it comes to Desktop experience.

I think you should look for a good linux laptop 1st and check for FreeBSD compatibility.

It could be a shock to you, but not everyone loves Mac OS X. There are (imagine that) other OSs that have terminals too.

Oh snap! I must've stroke a chord. What did I say? I mean, he asks how to grill a steak, but some suggest how to cook brats.

It's not about Facebook clone, they still use MySQL for some functionality (i believe), but not as RDBMS but more like NoSQL...

NoSQL means model your data in a different way, the way you'll be using it. For some it makes more sense, for some may not.

For example, compare implementation of a tagging system in mongo and any other RDBMS, which one is easier?

It may be hype, but when MongoDB was released, what other RDBMS was offering the same functionality? I see Posgresql + JSON mentioned, but when was JSON support added?

I personally like MongoDB for: - flexible schema (less migration pain) - easy tags implementation - product attributes (list of name-value pairs) - GridFS - store binary files - nested documents for analytics (ex: a record for each day with a nested doc for each hour)

I wish MongoDB had - some support of join - multi-master replication

I personally used MongoDB as primary storage (yeay dot me), but currently prefer it as secondary storage.

As any product it evolves and I expect to see more improvements. I think MongoDB brought NoSQL to the masses :)

Just my 0.02. Thanks.

yes, because all these third world countries have a good record of keeping a good log on what's going on...

Call me paranoid, but all "FDA approved" means is that I won't die right away

Can you give a few examples, please? I've been using Fedora as my primary home and work OS, since v14 and was gradually upgrading it and so far I never needed to compile anything.

How is this different from what BoA's ShopSafe? I've been using "virtual" cc for a few years now, that is the main reason I'm with BoA at the moment...

The only thing is that it's a bit of hassle to use their tool.

Also, I get a notification when my cc is used online or phone...

For some financial satisfaction comes 2nd.

Hey guys, author here. After being a long time free-rider, I thought to give back something useful.

Thanks for trying! Don't forget to check 'samples' dir. It should help you make an opinion.

Every time I see a post like this, I see lots of folks are super exited, but I still fail to see benefits, perhaps is the nature of my/our architecture/setup.

So, let's say I have a fairly typical setup, 1 web app, 1 database. Normally I would have 2 VM instances to start with. When I need to scale I add more nodes for web and/or db... both are load balanced, of course.

How would docker help me? I guess I should google for docker use cases, but I thought I'll try my luck here too.

Test/dev environments are pretty close to production ones.

It seems there is a lot of hype, but I fail to see it through. I'm wondering if all this hype is artificial, time will tell of course.

Thanks.

Thanks for trying to explain.

In my mind scale means use more resources, but in this case I fail to see benefits, except quicker env setup for the app, but for that there are automation services.

Yes, cluster-aware apps, if I want to scale 1 app, I'll create dedicated nodes/vm instances for it, how are containers helping? Why woudl I need multiple containers on the same host, for each app instance?

Thanks again.

Yes, I can see a great deal of benefits for development part, _if_ you're sticking with the same OS. Currently I have a bunch VMs (using kvm/qemu + libvirt) that are created and dropped as needed. The biggest advantages I see is that I can create a near identical environment with our VPSs... + I can test different OSs too (Linuxe vs *BSD).

My current pain point is the hdd space, since I have to resize VMs storage when needed. Even though it was automated, but still I'd prefer to use some shared hdd space and not to worry about it.

So, basically to achieve this you need to run production env using docker too? So that docket could match it.

Also, production data has to be copied over separately?

Are these correct assumptions?

PS: I'm still trying to understand how docket/containers may fit in current process.

I don't understand the part with scaling with containers on the same host. I mean if it's the same host, what kind of scaling is it?

"I’ll hop off my projects with deadlines and build something that I know probably won’t ever even get finished, but that I’m just excited to build."

That's sooo me... I always tell myself and my wife that these keep me sane.

PS: I don't drink coffee or mt dew though...

Why one would need docs if there are plenty of 100-200$/hours oracle consultants :)

I'm confused, the article gives Cassandra as an example of better data handling, but according to http://wiki.apache.org/cassandra/ArchitectureOverview and http://www.datastax.com/documentation/cassandra/2.0/webhelp/... you have eventual consistency and you get to tune consistency level... which setting is the same, but behaves better than mongo's?

PS: I'm not a fan, but I like mongo for what it gives... + I'm hoping it will get just better.

Good luck with this motto :) A penny saved is a penny earned!

The part with update check is interesting.

Java! My current stack is spring mvc 3, spring-data-mongodb. It's not perfect, but at least I don't have to hack my way into basic db ops...

So, if I have 30 nodes and my data is sharded between them, how is that better than having app/client side join, where I have more control what to fetch and what not? I could potentially cache results.

I mean, you realize if data is distributed at large scale, it may take a while till it gets from all nodes the data and joins it...

Java in particular... I don't want to use a small community supported driver in production. Which may be the reason that popular frameworks will not release support until there is one.

I just trying to compare with my current stack spring mvc 3, spring data mongodb.