Does anyone here can help me compare the price/month of these two elasticsearch hosting services?
Specifically, what is the equivalent of the Bonsai10 that costs $50/month when compared to the amazon elasticsearch pricing?
I just want to know which of the two services saves me money on a monthly basis for my rails app.
Thanks!
Bonsai10 is 8 core 1GB memory 10GB disk, limited to 20 shards & 1 million documents.
Amazon's AES doesn't have comparable sizing/pricing. All will be more expensive.
If you want 10GB of storage, you could run a single m3.large.elasticsearch (2 core 7.5GB memory, 32GB disk) at US$140/month.
If you want 8 cores, single m3.2xlarge.elasticsearch (8 core 30GB memory, 160GB disk) at US$560/month.
Elastic's cloud is more comparable. 1GB memory 16GB disk will run US$45/month. They don't publish the CPU count.
Out of the other better hosted elasticsearch providers (because they list actual resources you receive, full list below), qbox offers the lowest cost comparable plan for US$40/month for 1GB memory 20GB disk. No CPU count https://qbox.io/pricing
Objectrocket
Compose.io (an IBM company)
Qbox
Elastic
Related
Planning to subscribe Aura cloud managed services with memory 4GB, 0.8 CPU and 8 GB storage plan.
But the storage is not enough. Is it possible to increase the storage in this plan?
How many core of CPUs in this plan if its mentioned as 0.8 CPU?
The Aura pricing structure is very simple. You can increase storage (or memory or CPU) by paying for a higher-priced tier. Of course, you can contact Neo4j directly to ask if they have any other options.
0.8 CPU means that you get the equivalent of 80% of a single core.
You can get more details from the Aura knowledge base and developer guide.
What do I get by running multiple nodes on a single host? I am not getting availability, because if the host is down, the whole cluster goes with it. Does it make sense regarding performance? Doesn't one instance of ES take as many resources from the host as it needs?
Generally no, but if you have machines with ridiculous amounts of CPU and memory, you might want that to properly utilize the available resources. Avoiding big heaps with Elasticsearch is a good thing generally since garbage collection on bigger heaps can become a problem and in any case above 32 GB you lose the benefit of pointer compression. Mostly you should not need big heaps with ES. Most of the memory that ES uses is through memory mapped files, which relies on the OS cache. So just because you aren't assigning memory to the heap doesn't mean it is not being used: more memory available for caching means you'll be able to handle bigger shards or more shards.
So if you run more nodes, that advantage goes away and you waste memory on redundant heaps, and you'll have nodes competing for resources. Mostly, you should base these decisions on actual memory, cache, and cpu usage of course.
It depends on your host and how you configure your nodes.
For example, Elastic recommends allocating up to 32GB of RAM (because of how Java compresses pointers) to elasticsearch and have another 32GB for the operating system (mostly for disk caching).
Assuming you have more than 64GB of ram on your host, let's say 128, it makes sense to have two nodes running on the same machine, having both configured to 32GB ram each and leaving another 64 for the operating system.
I have three node CouchDB cluster. It is running on windows. Each node has 16vcpu and 64GB RAM. I am fairly new to CouchDB and to nonrelational databases in general.
The cluster is running on windows. What I am struggling with is one of the nodes (which I am assuming is the coordinator) is using the page file about 120GB disk space while it has about 48GB free RAM available to it.
We increased the RAM from 32Gb to 64GB to help with the paging. Only to find out that, it is now using more of the page file since the page file is being currently managed by the Windows OS.
I would assume it would be paging once it used all the available RAM, but what we have is 120GB paging file while it has about 50GB free RAM.
Why is it using the page file which has less response time while it has free RAM available to it?
Wasn't it supposed to use unreserved RAM for disk caching of frequently accessed DB file blocks to speed up access? Why is it behaving this way?
Is there a CouchDB or Erlang Beam configuration setting that I should be looking at?
I'd like to use a neo4j database in a docker container with Odroid XU4. The database is not big, approximately 20.000 nodes will be in it. The Odroid has only 2G memory, and I'd like to have a samba server, some nodejs applications and at least one PgSQL database too, so the system is short on memory. I read in the neo4j manual that 2G memory is the minimum, but I read by docker examples that it is used with 512M, so I am a little confused about this. What is the minimum memory I can use the neo4j docker image with?
I have similar troubles with the disk space. The system is on a 32GB SD card. I'd like to save database data there and backup on an external hard drive, so I could spend max 16GB for the neo4j. The data certainly does not require that kind of space, I am not sure why neo4j needs it (according to the manual again).
First you can use http://neo4j.com/hardware-sizing-calculator/ to get rough estimate for memory and disk usage.
Second option is to do some math. You can use information on page 12 in http://graphaware.com/assets/bachman-msc-thesis.pdf
You should keep in mind it's good to have all data in the memory for the performance reasons.
From my point of view you shouldn't have problem with the memory, but you can't expect great performance.
It's better to try it by yourself before you ask here ;)
I went through documentation of Passenger to find out how many application instances it can run with respect to hardware configuration. Documentation only talks about RAM
The optimal value depends on your system’s hardware and the server’s average load. You should experiment with different values. But generally speaking, the value should be at least equal to the number of CPUs (or CPU cores) that you have. If your system has 2 GB of RAM, then we recommend a value of 30. If your system is a Virtual Private Server (VPS) and has about 256 MB RAM, and is also running other services such as MySQL, then we recommend a value of 2.
It says minimum value can be number of CPU/CPU Cores we have. I have a VPS with one VCPU & 1GB RAM & my service provider has an option to just upgrade the RAM. I'm wondering how far I can just keep upgrading only RAM? How important it is to upgrade number of CPUs?
Quick Answer
Depends on what resources are the bottleneck for your app.
Long answer
You'll need to factor in a few things:
How much CPU time does your app need?
How much RAM does any given instance of your app use at peak load?
Does your app spend a lot of time doing IO intensive tasks? (ie: db and file reads/writes, network communication)
There can be other things to factor in, but your bottlenecks will probably be one of the above. If RAM is your main bottleneck, by all means use your newly available RAM. However, if it turns out that your app is being slowed down by CPU availability or flooded IO, no amount of RAM is going to speed things up.
On the topic of CPU cores; my understanding is that the main Apache process that runs Passenger is a single threaded process. Apache spawns new threads to handle concurrency on an as-needed basis. Each additional CPU core theoretically allows you to spawn x*n threads, where x is the number of threads you can optimally run under a single CPU core and n is the number of CPU cores available to Apache.
Disclaimer: I'm not very well read on Passenger internals; though this logic usually holds true for other kinds of Apache configurations.