We are working on one custom project management application on top of Moqui framework. Our requirement is, we need to inform any changes in ticket to the developers associated with the project through email.
Currently we are using WorkEffortParty entity to store all parties associated with the project and then PartyContactMech entity to store their email addresses. Here we need to iterate through WorkEffortParty and PartyContactMech everytime to fetch all email address to which we need to send emails for changes in tickets every time.
To avoid these iterations, we are now thinking of giving feature to add comma separated email addresses at project level. Project admin can add email addresses of associated parties or mailing list address to which he needs to send email notification for ticket change.
For this requirement, we studied around the data model but we didn't got the right place to store this information. Do we need to extend any entity for this or is there any best practice for this? This requirement is very useful in any project management application. We appreciate any help on this data modeling problem.
The best practice is to use existing data model elements as they are available. Having a normalized data model involves more work in querying data, but also more flexibility in addressing a wide variety of requirements without changes to the data structures.
In this case with a joined query you can get a list of email addresses in a single query based on the project's workEffortId. If you are dealing with massive data and message volumes there are better solutions than denormalizing source data, but I doubt that's the case... unless you're dealing with more than thousands of projects and millions of messages per day the basic query and iterate approach will work just fine.
If you need to go beyond that the easiest approach with Moqui is to use a DataDocument and DataFeed to send updates on the fly to ElasticSearch, and then use it for your high volume queries and filtering (with arbitrarily complex filtering, etc requirements).
Your question is way too open to answer directly, data modeling is a complex topic and without good understanding of context and intended usage there are no good answers. In general it's best to start with a data model based on decades of experience and used in a large number of production systems. The Mantle UDM is one such model.
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I’m trying to build a mobile app that involves users following each other. I’ve seen posts (here) that say it is a cardinal sin to store a users’ followees and followers as a list in a SQL database as each “cell” should only store one discrete value.
However, is this the case for noSQL, document-based databases? What are the pros and cons of storing followers and followees as a list in the user document, vs storing it in a separate collection?
The only ones i can see now is that retrieving the follower/followee data (could be?) faster for the former method as you don’t have to index the entire follower/followee collection, unlike the latter method (or is the time difference negligible?). On the other hand, one would require 2 writes every time someone follows/unfollows another user, which may be disadvantageous for billing in cloud databases, but might not be a problem if the database is hosted locally (?)
I’m very new to working with databases so I’m hoping to get some insight from more experienced people about long term/large scale effects of this choice. Thanks!
I am working at a company that merged with another company a while ago.
There we have several business units that are basically equivalent. One in Europe, one in China, each. We already had an in-house MariaDB database, which we want to start sharing.
The problem is that there are different GDPR regulations and contracts that prohibit sharing certain data across sites. So what I can't do, is replicate data across sites and then just hide in from the user in the frontend. The private data has to stay at the facility, it belongs to.
So my idea was to separate each table that we have now and where possibly sensitive information is contained into two tables each.
One say table_contracts_private and table_contracts_public.
This would still seem pretty doable with basic database replication and replicating the public tables across sites. But how would you go about publishing private data? Also how would I best combine private and public data? Just using a view
I just could not find any good mechanisms for this, especially because we would also like to avoid data duplication, so the private entries would need to be removed and replaced by the public ones, which would entail also changing all referencing IDs.
Is this a possible application of sharding?
I'd be really grateful, if someone could point me in the right direction, or if someone has a demo project with similar requirements that I could check out.
Cheers
Is this a possible application of sharding?
I wouldn't think so. Sharding is a performance optimization method. What you need is to support legal constraints. Those are two very different problems.
I think you are on the right track. I call this a "walled garden" approach. You create a database with all non-PII information, using ids only. Nothing that remotely directly identifies people, their addresses, phones, credit cards, and so on. This can be tricky. In some jurisdictions combinations of demographics can be PII.
Some of those ids then refer to another database where you store all the sensitive information; this is the "walled garden". I would recommend that this second database be on a separate server. It has a very restricted access list. And this is where you implement requirements for things like "forgetting" a customer.
In any case, the point is that sharding is not the right approach. You want an application redesign with privacy and security as the top priorities. Happily, this is not actually that hard to implement, although if the databases are changing, you may need period auditing. For instance, in one database I worked with, we discovered that "coupon codes" sometimes contained unencrypted email addresses. Arrgggh!
I'm currently trying to figure out how to use blockchain in audit trails and potentially in accounting (and if they actually make sense). Both Deloitte and EY mention them.
I somehow cannot understand how this could be of benefit for audits and/or accounting.
To my understanding to make use of the power of blockchains you need multiple users. Only one user means you cannot validate the integrity since all blocks of that user could be compromised (if one block of a blockchain of a user got changed maybe also all of the following where changed, making it impossible to detect the modification). This means blockchains only make sense if you can share them with different users?
Data and thus blockchains however aren't always shared between multiple users. In accounting you often only have one "user"/"owner" of the data. Sure you could create multiple users in one company but there wouldn't be any benefit since they are in one location (company) and potentially all compromised. Or if the admin want's to change something he could easily modify all users making it useless for audits.
To make it work you would need different partners (supplier/customer) to share the information with. In that case you could however only have two users share the same blockchain (depending on legal regulations in your country) and then again who do you trust if one of the two doesn't validate?
Deloitt mentions that they can be used for files. Again I don't see the benefit since you would need multiple users AND files might get compressed with a different algorithm over time rendering them invalid (the useful information didn't change but the block will still be invalid). Or is this a not an issue from your experience? To me it seems it could be a problem.
The same goes for all the internal data which may be important for audits from my point of view. Which company would like to share the information with independent users. Or is it only intendet for "public"/"shared" data?
To identify a modification of one block in a blockchain the user would have ot validate every single block (every hash in the header of a block needs to be compared to the data of the previous block). In terms of accounting a blockchain could be all transactions of one account during one fiscal year. This however could easily be thousands of transactions. Wouldn't this be very slow to validate?
Maybe I'm misunderstanding the point in terms of audit trails but as long as the users are not independent data can always be modified making it useless for audits. And you need a critical mass to share the blockchain with.
First of all, I think that it's neccesary to get the power of Blockchain. It gives us the chance to create descentralized data bases, i.e. data bases that are not controled by an authority. Also, the data of Blockchain is immutable and permanent, i.e. it can not be modified or deleted. Thanks to it you achive a unique descentralized registry in a distributed network, for example for audit trails.
It's true that it has no sense if you use it inside your company. But if you use it among different companies? Each one could encode its data, so the rest of the companies couldn't see it. However, all the data would be stored in all the companies, so anyone couldn't change it. Moreover, you can have more than one user (node) for each company.
Nowadays, there are many implementations of Blockchain, each one with a different objetive. To understan better the power of Blockchain, I suggest you to wathc the video were is explained the new version (the v 1.0) of the Hyperledger Fabric.
I'm currently working in a Silverlight / MS SQL project where the Entity Framework has not been implemented and I would like to know what's the best practice to deal with calculated fields in this particular situation.
Considering that some external system might also consume my data directly in the DB or thru a web service, here's the 3 options I can see right now.
1) Force any external system to consume data thru a web service and create all the calculated fields in the objects only.
2) Create the calculated fields in a DB view and resync your object with the server each time a value needs to be calculated.
3) Replicate the calculation rules in the object and the database view.
Any other suggestions would also be welcomed.
I would recommend to follow two principles: data decoupling and minimum functionality duplication. Both would suggest to put your calculations in one place only, and serve them already calculated. So I would implement the calculations in the DB, and serve them via a web service.
However, you have to consider your particular case. For example, if the calculations are VERY heavy, you could delegate them to the client to spare server resources. This could even be the reason you are using Silverlight. I am in a similar situation on a project, and I found that the best compromise is to push raw data to the client and have it do the heavy computations.
Having a best practice or approach for this kind of problem is difficult as circumstances change what was formerly a good approach might start to seem less useful. That said where possible I would do anything data related at the DB level including calculated fields. This way you know no matter where you are looking at the data from you will see the same results. So your web service, SQL reporting and anything else that needs to look at or receive data will see the same result.
We're building a Silverlight application which will be offered as SaaS. The end product is a Silverlight client that connects to a WCF service. As the number of clients is potentially large, updating needs to be easy, preferably so that all instances can be updated in one go.
Not having implemented multi tenancy before, I'm looking for opinions on how to achieve
Easy upgrades
Data security
Scalability
Three different models to consider are listed on msdn
Separate databases. This is not easy to maintain as all schema changes will have to be applied to each customer's database individually. Are there other drawbacks? A pro is data separation and security. This also allows for slight modifications per customer (which might be more hassle than it's worth!)
Shared Database, Separate Schemas. A TenantID column is added to each table. Ensuring that each customer gets the correct data is potentially dangerous. Easy to maintain and scales well (?).
Shared Database, Separate Schemas. Similar to the first model, but each customer has its own set of tables in the database. Hard to restore backups for a single customer. Maintainability otherwise similar to model 1 (?).
Any recommendations on articles on the subject? Has anybody explored something similar with a Silverlight SaaS app? What do I need to consider on the client side?
Depends on the type of application and scale of data. Each one has downfalls.
1a) Separate databases + single instance of WCF/client. Keeping everything in sync will be a challenge. How do you upgrade X number of DB servers at the same time, what if one fails and is now out of sync and not compatible with the client/WCF layer?
1b) "Silos", separate DB/WCF/Client for each customer. You don't have the sync issue but you do have the overhead of managing many different instances of each layer. Also you will have to look at SQL licensing, I can't remember if separate instances of SQL are licensed separately ($$$). Even if you can install as many instances as you want, the overhead of multiple instances will not be trivial after a certain point.
3) Basically same issues as 1a/b except for licensing.
2) Best upgrade/management scenario. You are right that maintaining data isolation is a huge concern (1a technically shares this issue at a higher level). The other issue is if your application is data intensive you have to worry about data scalability. For example if every customer is expected to have tens/hundreds millions rows of data. Then you will start to run into issues and query performance for individual customers due to total customer base volumes. Clients are more forgiving for slowdowns caused by their own data volume. Being told its slow because the other 99 clients data is large is generally a no-go.
Unless you know for a fact you will be dealing with huge data volumes from the start I would probably go with #2 for now, and begin looking at clustering or moving to 1a/b setup if needed in the future.
We also have a SaaS product and we use solution #2 (Shared DB/Shared Schema with TenandId). Some things to consider for Share DB / Same schema for all:
As mention above, high volume of data for one tenant may affect performance of the other tenants if you're not careful; for starters index your tables properly/carefully and never ever do queries that force a table scan. Monitor query performance and at least plan/design to be able to partition your DB later on based some criteria that makes sense for your domain.
Data separation is very very important, you don't want to end up showing a piece of data to some tenant that belongs to other tenant. every query must have a WHERE TenandId = ... in it and you should be able to verify/enforce this during dev.
Extensibility of the schema is something that solutions 1 and 3 may give you, but you can go around it by designing a way to extend the fields that are associated with the documents/tables in your domain that make sense (ie. Metadata for tables as the msdn article mentions)
What about solutions that provide an out of the box architecture like Apprenda's SaaSGrid? They let you make database decisions at deploy and maintenance time and not at design time. It seems they actively transform and manage the data layer, as well as provide an upgrade engine.
I've similar case, but my solution is take both advantage.
Where data and how data being placed is the question from tenant. Being a tenant of course I don't want my data to be shared, I want my data isolated, secure and I can get at anytime I want.
Certain data it possibly share eg: company list. So database should be global and tenant database, just make sure to locked in operation tenant database schema, and procedure to update all tenant database at once.
Anyway SaaS model everything delivered as server / web service, so no matter where the database should come to client as service, then only render by client GUI.
Thanks
Existing answers are good. You should look deeply into the issue of upgrading and managing multiple databases. Without knowing the specific app, it might turn out easier to have multiple databases and not have to pay the extra cost of tracking the TenantID. This might not end up being the right decision, but you should certainly be wary of the dev cost of data sharing.