We certainly want to use separate databases since the front-end team finds it robust to work with MongoDB Atlas and AWS cloud architects find it easy to work with DynamoDB.
Our architecture:
Web application uses MongoDB to insert, update and retrieve data.
The MongoDB is synced in real-time with DynamoDB.
Background AWS services use DynamoDB for inserting, updating and retrieving data.
The changes in either DynamoDB or MongoDB are replicated to each other.
Tried so far:
We currently do have a sync in place with DyanmoDB streams and MongoDB atlas trigger to listen to changes on each database and forward them to the other. We use lambas for this, but our replication logic is not robust yet.
AWS Database Migration Service with ongoing replication has been suggested but haven't been able to get it to work in our use case. Perhaps, this is one option.
3rd party services like: https://www.cdata.com/sync/
Ideal Fit
The most ideal solution would be an AWS-based solution if not a reliable 3rd party service.
Greatly appreciate any resources or thoughts on this! :)
Looking to build a react-native app and was going to use MongoDB Atlas for the database, express/apollo/graphql mixed in there for better querying. Has anyone had any experience with these techs together? especialy MongoDB Atlas and express?
I'm not sure how all these techs link together. Any tutorials will be handy as well. Thanks.
MongoDB Atlas provides you the endpoint where you can connect to the replica set and use mongodb.
This takes over many other factors such as installing mongodb, backups and restore. Also, the endpoint(connection string) provided by MongoDB Atlas comes with built-in:
Authentication enabled
Authorized users
Replica set to maintain HA
All of these factors give you advantages of using MongoDB Altas so that you can focus on developing your apps
Using mongodb atlas is likely to give you same things you would expect from your local mongodb and express with additional advantages listed above
If you're planning on using MongoDB and GraphQL in a NodeJs service in the interest of getting better querying capabilities, I'd suggest looking at GraphQL-to-MongoDB, or how I learned to stop worrying and love generated query APIs.
Disclaimer: I wrote that blog post.
MongoDB Atlas just announced GraphQL support for Atlas and Stitch. In a nutshell , you can easily generate/ create Schema for a collection in Atlas, Define access rules, relations and generate queries and mutations. GraphiQL is also integrated to run and test your queries. Check this blog post for more details - https://www.mongodb.com/blog/post/introducing-graphql-support-in-mongodb-atlas-with-stitch
I knew MongoDB and Google Cloud Datastore offer NoSQL database systems. I'm new to deploying a database. These are some of my confusions:
How do we compare the cost of running MongoDB in Google Compute Engine vs. using Google Cloud Datastore? Can you quote a small example estimate? We may find many related articles. But I couldn't find one that address this specific question.
I came to know about the Click to Deploy option in Compute Engine. What is the difference(in cost/performance) between manually configuring the Compute Engine for MongoDB and Click to Deploy option?
Within the Click to Deploy option you'll find two options(this and this) we can choose for MongoDB. Can you spot the difference between them? There is also a significant price difference between them.
Is it worthy to start developing in Google Cloud Datastore leaving my MongoDB skills?
I would prefer to know the answers on the basis of cost, development overhead and perfomance.
We are currently investigating the options to make a partly switch to Google Cloud SQL. What we are searching for is a setup by which data is available for reading in multiple regions to increase the speed of the web-application. Writing from multiple regions would off course be great, but that's not really something MySQL does when you also want to have speed on your side :-)
What we would like to setup is a master-slave setup through which the Master would be in Europe and slaves (for reading) would be available in the US and Asia. This way we can provide information to our customers from a VM + SQL instance in Asia without having to connect to a database in Europe.
As far as I am aware it is not possible to currently add a read-instance outside of the region of the master. Is that correct?
Or, would it be possible to create our own MySQL read-only instance and let it replicate from a Google Cloud SQL instance? This would not be preferable (database administration, server administration) but is off course an option.
You can do cross-region replication in Cloud SQL, although it is not straight forward because the performance will not be great. You have to create a master in Cloud SQL, then create a replica with external master pointing at the master you created: https://cloud.google.com/sql/docs/replication#external-master
You can go in the other direction as well: https://cloud.google.com/sql/docs/replication#replication-external
These features are only supported for first generation of Cloud SQL.
Cloud Spanner is a relational database that supports transactional consistency on a global scale. It is an SQL Database and works great in a Multi-region environment. Therefore, It can be a good choice for your case. For more info, please check https://cloud.google.com/spanner/
I want to use a NoSQL database on Windows Azure and the data volume will be very large. Whether a Azure Table storage or a MongoDB database running using a Worker role can offer better performance and scalability? Has anyone used MongoDB on Azure using a Worker role? Please share your thoughts on using MongoDB on Azure over the Azure table storage.
Table Storage is a core Windows Azure storage feature, designed to be scalable (100TB 200TB 500TB per account), durable (triple-replicated in the data center, optionally georeplicated to another data center), and schemaless (each row may contain any properties you want). A row is located by partition key + row key, providing very fast lookup. All Table Storage access is via a well-defined REST API usable through any language (with SDKs, built on top of the REST APIs, already in place for .NET, PHP, Java, Python & Ruby).
MongoDB is a document-oriented database. To run it in Azure, you need to install MongoDB onto a web/worker roles or Virtual Machine, point it to a cloud drive (thereby providing a drive letter) or attached disk (for Windows/Linux Virtual Machines), optionally turn on journaling (which I'd recommend), and optionally define an external endpoint for your use (or access it via virtual network). The Cloud Drive / attached disk, by the way, is actually stored in an Azure Blob, giving you the same durability and georeplication as Azure Tables.
When comparing the two, remember that Table Storage is Storage-as-a-Service: you simply access a well-known REST endpoint. With MongoDB, you're responsible for maintaining the database (e.g. whenever MongoDB Inc (formerly 10gen) pushes out a new version of MongoDB, you'll need to update your server accordingly).
Regarding MongoDB Inc's alpha version pointed to by jtoberon: If you take a close look at it, you'll see a few key things:
The setup is for a Standalone mongodb instance, without replica-sets or shards. Regarding replica-sets, you still get several benefits using the Standalone version, due to the way Blob storage works.
To provide high-availability, you can run with multiple instances. In this case, only one instance serves the database, and one is a 'warm-standby' that launches the mongod process as soon as the other instance fails (for maintenance reboot, hardware failure, etc.).
While 10gen's Windows Azure wrapper is still considered 'alpha,' mongod.exe is not. You can launch the mongod exe just like you'd launch any other Windows exe. It's just the management code around the launching, and that's what the alpa implementation is demonstrating.
EDIT 2011-12-8: This is no longer in an alpha state. You can download the latest MongoDB+Windows Azure project here, which provides replica-set support.
For performance, I think you'll need to do some benchmarking. Having said that, consider the following:
When accessing either Table Storage or MongoDB from, say, a Web Role, you're still reaching out to the Windows Azure Storage system.
MongoDB uses lots of memory for its own cache. For this reason, lots of high-scale MongoDB systems are deployed to larger instance sizes. For Table Storage access, you won't have the same memory-size consideration.
EDIT April 7, 2015
If you want to use a document-based database as-a-service, Azure now offers DocumentDB.
I have used both.
Azure Tables : dead simple, fast, really hard to write even simple queries.
Mongo : runs nicely, lots of querying capabilities, requires several instances to be reliable.
In a nutshell,
if your queries are really simple (key->value), you must run a cost comparison (mainly number of transactions against the storage versus cost of hosting Mongo on Azure). I would rather go to table storage for that one.
If you need more elaborate queries and don't want to go to SQL Azure, Mongo is likely your best bet.
I realize that this question is dated. I'd like to add the following info for those who may come upon this question in their searches.
Note that now, MongoDB is offered as a fully managed service on Azure. (officially in Beta as of Apr '15)
See:
http://www.mongodb.com/partners/cloud/microsoft
or
https://azure.microsoft.com/en-us/blog/announcing-new-mongodb-instances-on-microsoft-azure/
See (including pricing):
https://azure.microsoft.com/en-us/marketplace/partners/mongolab/mongolab/
My first choice is AzureTables because SAAS model and low cost and SLA 99.99% http://alexandrebrisebois.wordpress.com/2013/07/09/what-if-20000-windows-azure-storage-transactions-per-second-isnt-enough/
some limits..
http://msdn.microsoft.com/en-us/library/windowsazure/jj553018.aspx
http://www.windowsazure.com/en-us/pricing/calculator/?scenario=data-management
or AzureSQL for small business
DocumentDB
http://azure.microsoft.com/en-us/documentation/services/documentdb/
http://azure.microsoft.com/en-us/documentation/articles/documentdb-limits/
second choice is many cloud providers including Amazon offer S3
or Google tables https://developers.google.com/bigquery/pricing
nTH choice manage the SHOW all by myself have no sleep MongoDB well I will look again the first two SAAS
My choice if I am running "CLOUD" I will go for SAAS model as much as possible "RENT-IT"...
The question is what my app needs is it AzureTables or DocumentDB or AzureSQL
DocumentDB documentation
http://azure.microsoft.com/en-us/documentation/services/documentdb/
How Azure pricing works
http://azure.microsoft.com/en-us/pricing/details/documentdb/
this is fun
http://www.documentdb.com/sql/demo
At Build 2016 it was announced that DocumentDB would support all MongoDB drivers. This solves some of the lack of tooling issues with DocDB and also makes it easier to migrate Mongo apps.
Above answers are all good - but the real answer depends on what your requirements are. You need to understand what size of data you are processing, what types of operations you want to perform on the data and then select the solution that meets your needs.
One thing to remember is Azure Table Storage doesn't support complex data types.It supports every property in entity to be a String or number or boolean or date etc.
One can't store an object against a key,which i feel is must for NoSql DB.
https://learn.microsoft.com/en-us/rest/api/storageservices/fileservices/understanding-the-table-service-data-model scroll to Property Types