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I am going to use mongodb, but being a .net developer I am looking into
Azure Documentdb.
I want to know.
Anyone is really using Azure Documentdb on production.
Is azure Documentbd is as good as in performance as mongodb.
TIA.
Anyone is really using Azure Documentdb on production.
R: Microsoft is using on MSN portal and One Note.
Is azure Documentbd is as good as in performance as mongodb.
Yes, it is.
Mongo is more mature, but Azure DocumentDB is always being improved. I suppose that you are going to host your app on Azure, so I would go with Azure DocumentDB because it uses SSDs and I won't need to handle with the infrastructure stuff.
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I am exploring on schema registries, I have a Kafka setup and now I want to introduce schema support for producer and consumer. I found that both are supporting Avro format and have multiple compatibility options. I am new to both. Can anybody suggest me which one is better or could compare them both.
Thanks in advance!
While Glue works with Kafka, from what I've seen, it is more intended for usage with Athena and similar AWS data-analysis tools. It is serverless, so there is nothing to install and manage, and integrates with IAM, so you can manage permissions all within AWS.
Confluent's is only for Kafka and cannot be (easily) integrated with those other AWS tools.
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I want to know how to recover Scalar DB to another instance using Cassy backup.
Because I need a new instance for tests from the production environment.
There is no direct support in Cassy to load backups that were taken in a cluster to another cluster.
Since Cassy only manages snapshots of Cassandra, you can follow the doc to do it.
For testing, I would recommend dumping some of the data from the current (possibly production) cluster and load it to a new testing cluster.
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I installed Mongodb in EC2 t2.small instance with this guide. I don't know whether dedicate this instance for MonogoDB. or use this same instance for app deployment for production. Suggest me the best practice.
The 'best practice' is to run the database server on its on instance; the even better 'best practice' is to run MongoDB on a cluster of instances to give you high availability.
That said, its perfectably acceptable, imo, to run the DB and your app on the same instance for small projects with low demands where cost is an important driver, although personally I would use at least a EC2 large instance if you are going to make your instance do double-duty in this manner.
Now that you know what is 'best', only you can determine how much 'best' you can afford.
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I am considering using mongo db (it could be postgresql or any other ) as a data warehouse, my concern is that up to twenty or more users could be running queries at a time and this could have serious implications in terms of performance.
My question is what is the best approach to handle this in a cloud based and non cloud based environment? Do cloud based db's automatically handle this? If so would the data be consistent through all instances if a refresh on the data was made? In a non cloud based environment would the best approach be to load balance all instances? Again how would you ensure data integrity for all instances?
thanks in advance
I think auto sharding is what I am looking for
http://docs.mongodb.org/v2.6/MongoDB-sharding-guide.pdf
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AWS published a blog post about migrating from Parse. I wonder why they suggest hosting MongoDB on MongoLab instead of hosting it directly on AWS?
What's the advantage of hosting MongoDB on MongoLab?
If you have enough experience to manage mongodb yourself, and scale on your own, i think aws instances are cheaper than any hosted mongodb service. That depends on how many servers you will have to manage based on your requirement.
And another reason, since parse is a hosted service, that blog post is mostly for people looking for another hosted service.