I have been developing a network security application for several years now, as the lead developer at my company. It is a split-architecture design, where one component resides on the customer's network, and the other component in our own cloud. We have developed our own custom versioning system that keeps both sides synchronized at each patch (per customer), but until now it has only allowed incremental changes to be made, and rollbacks are not possible.
We'd like to move to a forkable git-like solution for our code, so that we can develop and test multiple features simultaneously, but the thing that's holding us back from that is our database. We use PostgreSQL (currently 9.3.12), and I've written a custom script to calculate the deltas between the "old" and "new" database structure, each time we "make a patch". It spits out a list of SQL commands necessary to update the "old" database structure to look like the "new", including tables, functions, sequences, triggers, you name it. It's very elegant and pretty much never fails anymore, even with complicated deltas.
However, I realize that in order to have a git-like solution for this (check-out, check-in, merge changes into test and production code, etc.) while also keeping database changes in sync with application code, we'll need to have something a lot more advanced than just "old" vs "new". Note that we don't need to modify database data for the most part, only table structure, which is altered in place on existing customer databases.
So my question is this: Any ideas for a git-like SQL version control system, which allows forking and merging, and can be easily kept in sync with application code changes? Our custom tool is already a bit more advanced than some open-source tools we've looked into (such as sqlt-diff), and tools like Red Gate are a bit out of our price range as a startup (not to mention that I haven't heard anybody mention forking in context with Red Gate). We're open to writing a custom tool, if that's what we need to do, but we're scratching our heads about where to start with something like that. We know how to calculate deltas, but we don't know how to manage all those things across different forks.
Free or open-source tools, frameworks we can adapt, or general guiding principles for building such tools are all appreciated!
One way of solving this problem is with migrations. A couple of lightweight tools, but there are many others:
http://sequel.jeremyevans.net/rdoc/files/doc/migration_rdoc.html
https://flywaydb.org/
Rather than calculating deltas between versions after the fact, migrations can be used to evolve the schema in a controlled way. You can create feature-specific migrations that can be tracked (and forked/merged) along with the rest of your code.
Depending on how fancy you want to get, you may need to extend the default naming/numbering schemes.
I need to be able to save all the data that gets updated like so.
User inserts a car Model (Make, Type, Year). Comes back and Updates the Year. I need to be able to save both so they have a history of all the work that they did. What is the best way to do that?
There are a number of ways to do this. One way is to write some SQL triggers and do it entirely in the database. Have a look here for some clues:
Another way is to do the auditing within the Entity Framework code. There is a nuget package called AuditDbContext with the source on Codeplex.
You need to decide if you want to do the auditing in EF or in SQL. Obviously if you need to audit everything and you might sometimes access the database from different applications which don't use the same EF datalayer (e.g. different technologies, etc), then SQL triggers might well be the way to go.
Maybe (if you are facing the "history" issue more often) the CQRS pattern is of interest for you; a good primer, Microsoft on CQRS. There is a framework build on .NET for this pattern (I have not tried it yet): NCQRS.
If you really just want the requirement in your question fulfilled now and you are using SQL Server 2010 or later, then Change Tracking may be another option. I would prefer that to triggers (but in the end all such dark processing logging solutions introduce additional risk).
I'm in the research phase trying to adopt 2012 Database Projects on an existing small project. I'm a C# developer, not a DBA, so I'm not particularly fluent with best practices. I've been searching google and stackoverflow for a few hours now but I still don't know how to handle some key deployment scenarios properly.
1) Over the course of several development cycles, how do I manage multiple versions of my database? If I have a client on v3 of my database and I want to upgrade them to v8, how do I manage this? We currently manage hand-crafted schema and data migration scripts for every version of our product. Do we still need to do this separately or is there something in the new paradigm that supports or replaces this?
2) If the schema changes in such a way that requires data to be moved around, what is the best way to handle this? I assume some work goes in the Pre-Deployment script to preserve the data and then the Post-Deploy script puts it back in the right place. Is that the way of it or is there something better?
3) Any other advice or guidance on how best to work with these new technologies is also greately appreciated!
UPDATE: My understanding of the problem has grown a little since I originally asked this question and while I came up with a workable solution, it wasn't quite the solution I was hoping for. Here's a rewording of my problem:
The problem I'm having is purely data related. If I have a client on version 1 of my application and I want to upgrade them to version 5 of my application, I would have no problems doing so if their database had no data. I'd simply let SSDT intelligently compare schemas and migrate the database in one shot. Unfortunately clients have data so it's not that simple. Schema changes from version 1 of my application to version 2 to version 3 (etc) all impact data. My current strategy for managing data requires I maintain a script for each version upgrade (1 to 2, 2 to 3, etc). This prevents me from going straight from version 1 of my application to version 5 because I have no data migration script to go straight there. The prospect creating custom upgrade scripts for every client or managing upgrade scripts to go from every version to every greater version is exponentially unmanageable. What I was hoping was that there was some sort of strategy SSDT enables that makes managing the data side of things easier, maybe even as easy as the schema side of things. My recent experience with SSDT has not given me any hope of such a strategy existing but I would love to find out differently.
I've been working on this myself, and I can tell you it's not easy.
First, to address the reply by JT - you cannot dismiss "versions", even with declarative updating mechanics that SSDT has. SSDT does a "pretty decent" job (provided you know all the switches and gotchas) of moving any source schema to any target schema, and it's true that this doesn't require verioning per se, but it has no idea how to manage "data motion" (at least not that i can see!). So, just like DBProj, you left to your own devices in Pre/Post scripts. Because the data motion scripts depend on a known start and end schema state, you cannot avoid versioning the DB. The "data motion" scripts, therefore, must be applied to a versioned snapshot of the schema, which means you cannot arbitrarily update a DB from v1 to v8 and expect the data motion scripts v2 to v8 to work (presumably, you wouldn't need a v1 data motion script).
Sadly, I can't see any mechanism in SSDT publishing that allows me to handle this scenario in an integrated way. That means you'll have to add your own scafolding.
The first trick is to track versions within the database (and SSDT project). I started using a trick in DBProj, and brought it over to SSDT, and after doing some research, it turns out that others are using this too. You can apply a DB Extended Property to the database itself (call it "BuildVersion" or "AppVersion" or something like that), and apply the version value to it. You can then capture this extended property in the SSDT project itself, and SSDT will add it as a script (you can then check the publish option that includes extended properties). I then use SQLCMD variables to identify the source and target versions being applied in the current pass. Once you identify the delta of versions between the source (project snapshot) and target (target db about to be updated), you can find all the snapshots that need to be applied. Sadly, this is tricky to do from inside the SSDT deployment, and you'll probably have to move it to the build or deployment pipeline (we use TFS automated deployments and have custom actions to do this).
The next hurdle is to keep snapshots of the schema with their associated data motion scripts. In this case, it helps to make the scripts as idempotent as possible (meaning, you can rerun the scripts without any ill side-effects). It helps to split scripts that can safely be rerun from scripts that must be executed one time only. We're doing the same thing with static reference data (dictionary or lookup tables) - in other words, we have a library of MERGE scripts (one per table) that keep the reference data in sync, and these scripts are included in the post-deployment scripts (via the SQLCMD :r command). The important thing to note here is that you must execute them in the correct order in case any of these reference tables have FK references to each other. We include them in the main post-deploy script in order, and it helps that we created a tool that generates these scripts for us - it also resolves dependency order. We run this generation tool at the close of a "version" to capture the current state of the static reference data. All your other data motion scripts are basically going to be special-case and most likely will be single-use only. In that case, you can do one of two things: you can use an IF statement against the db build/app version, or you can wipe out the 1 time scripts after creating each snapshot package.
It helps to remember that SSDT will disable FK check constraints and only re-enable them after the post-deployment scripts run. This gives you a chance to populate new non-null fields, for example (by the way, you have to enable the option to generate temporary "smart" defaults for non-null columns to make this work). However, FK check constraints are only disabled for tables that SSDT is recreating because of a schema change. For other cases, you are responsible for ensuring that data motion scripts run in the proper order to avoid check constraints complaints (or you manually have disable/re-enable them in your scripts).
DACPAC can help you because DACPAC is essentially a snapshot. It will contain several XML files describing the schema (similar to the build output of the project), but frozen in time at the moment you create it. You can then use SQLPACKAGE.EXE or the deploy provider to publish that package snapshot. I haven't quite figured out how to use the DACPAC versioning, because it's more tied to "registered" data apps, so we're stuck with our own versioning scheme, but we do put our own version info into the DACPAC filename.
I wish I had a more conclusive and exhasutive example to provide, but we're still working out the issues here too.
One thing that really sucks about SSDT is that unlike DBProj, it's currently not extensible. Although it does a much better job than DBProj at a lot of different things, you can't override its default behavior unless you can find some method inside of pre/post scripts of getting around a problem. One of the issues we're trying to resolve right now is that the default method of recreating a table for updates (CCDR) really stinks when you have tens of millions of records.
-UPDATE: I haven't seen this post in some time, but apparently it's been active lately, so I thought I'd add a couple of important notes: if you are using VS2012, the June 2013 release of SSDT now has a Data Comparison tool built-in, and also provides extensibility points - that is to say, you can now include Build Contributors and Deployment Plan Modifiers for the project.
I haven't really found any more useful information on the subject but I've spent some time getting to know the tools, tinkering and playing, and I think I've come up with some acceptable answers to my question. These aren't necessarily the best answers. I still don't know if there are other mechanisms or best practices to better support these scenarios, but here's what I've come up with:
The Pre- and Post-Deploy scripts for a given version of the database are only used migrate data from the previous version. At the start of every development cycle, the scripts are cleaned out and as development proceeds they get fleshed out with whatever sql is needed to safely migrate data from the previous version to the new one. The one exception here is static data in the database. This data is known at design time and maintains a permanent presence in the Post-Deploy scripts in the form of T-SQL MERGE statements. This helps make it possible to deploy any version of the database to a new environment with just the latest publish script. At the end of every development cycle, a publish script is generated from the previous version to the new one. This script will include generated sql to migrate the schema and the hand crafted deploy scripts. Yes, I know the Publish tool can be used directly against a database but that's not a good option for our clients. I am also aware of dacpac files but I'm not really sure how to use them. The generated publish script seems to be the best option I know for production upgrades.
So to answer my scenarios:
1) To upgrade a database from v3 to v8, I would have to execute the generated publish script for v4, then for v5, then for v6, etc. This is very similar to how we do it now. It's well understood and Database Projects seem to make creating/maintaining these scripts much easier.
2) When the schema changes from underneath data, the Pre- and Post-Deploy scripts are used to migrate the data to where it needs to go for the new version. Affected data is essentially backed-up in the Pre-Deploy script and put back into place in the Post-Deploy script.
3) I'm still looking for advice on how best to work with these tools in these scenarios and others. If I got anything wrong here, or if there are any other gotchas I should be aware of, please let me know! Thanks!
In my experience of using SSDT the notion of version numbers (i.e. v1, v2...vX etc...) for databases kinda goes away. This is because SSDT offers a development paradigm known as declarative database development which loosely means that you tell SSDT what state you want your schema to be in and then let SSDT take responsibility for getting it into that state by comparing against what you already have. In this paradigm the notion of deploying v4 then v5 etc.... goes away.
Your pre and post deployment scripts, as you correctly state, exist for the purposes of managing data.
Hope that helps.
JT
I just wanted to say that this thread so far has been excellent.
I have been wrestling with the exact same concerns and am attempting to tackle this problem in our organization, on a fairly large legacy application. We've begun the process of moving toward SSDT (on a TFS branch) but are at the point where we really need to understand the deployment process, and managing custom migrations, and reference/lookup data, along the way.
To complicate things further, our application is one code-base but can be customized per 'customer', so we have about 190 databases we are dealing with, for this one project, not just 3 or so as is probably normal. We do deployments all the time and even setup new customers fairly often. We rely heavily on PowerShell now with old-school incremental release scripts (and associated scripts to create a new customer at that version). I plan to contribute once we figure this all out but please share whatever else you've learned. I do believe we will end up maintaining custom release scripts per version, but we'll see. The idea about maintaining each script within the project, and including a From and To SqlCmd variable is very interesting. If we did that, we would probably prune along the way, physically deleting the really old upgrade scripts once everybody was past that version.
BTW - Side note - On the topic of minimizing waste, we also just spent a bunch of time figuring out how to automate the enforcement of proper naming/data type conventions for columns, as well as automatic generation for all primary and foreign keys, based on naming conventions, as well as index and check constraints etc. The hardest part was dealing with the 'deviants' that didn't follow the rules. Maybe I'll share that too one day if anyone is interested, but for now, I need to pursue this deployment, migration, and reference data story heavily. Thanks again. It's like you guys were speaking exactly what was in my head and looking for this morning.
So I'm new to Core Data, everything I read says to use it - if you use SQLite you're an evil bad person. But I'm lost on some simple things. I have a bunch of data that will be used to setup a NSCollectionView, this would be relatively simple in SQLite, but I don't want to be an evil bad person. Is there a simple tutorial someplace that I'm missing? I would love to see a example SQL database based app and the same thing with core data.
Something like here is a table structure in SQL, here is the equivalent in core data...
Here is a INSERT script in SQL, here is the equivalent in core data...
Here is a SELECT with a JOIN and a few WHERE statements, here is the equivalent in core data...
Its even the little things that I don't understand.
How do I provide a pre-populated core data system
Where do the core data files live? in the bundle like my SQLite database would?
With an update to the app what do I have to do to update the core data files if they live outside my bundle?
Justin808,
No one is an "evil bad person" for not using CD. If you prefer to use SQLite, go for it. It is used by many applications. It is a framework. If SQLite is a technology you are used to, then use SQLite. That said, CD is the Apple encouraged path for building rich, persistent model apps on their platforms. They don't provide many tools for the pure SQL community but provide a very rich set of tools for CD apps. I've attempted to answer the technology question here: Core Data VS Sqlite or FMDB…?
About your request for a line by line comparison between the same app implemented both ways, this sounds like an excellent learning opportunity for you to write one. (I teach beginning iOS programming. The app you're asking for can be quite simple. You can probably write both versions in one weekend. I would be happy to review your work and critique your blog post describing the differences. You could make an excellent contribution to other folks in your situation trying to choose between these two technologies.)
Your questions:
Something like here is a table structure in SQL, here is the
equivalent in core data...
Schemas are described differently but are substantially similar. That said, an SQL schema may not be tuned for use by CD and/or UI application or vice versa.
Here is a INSERT script in SQL, here is the equivalent in core data...
There are plenty of examples by Apple and others that tell you how to insert new entities. What is it you don't understand?
Here is a SELECT with a JOIN and a few WHERE statements, here is the
equivalent in core data...
The predicate language in CD is different than SQL. As such, you will query things differently. In particular, CD is an almost "pure" set theoretic approach to organizing data. You use fetches to seed your "query" and set operation to refine it. Beyond that, I need to direct you to one of the many books about CD and its predicate language.
How do I provide a pre-populated core data system
CD depends upon a file like every other DB system. You provide it in your bundle and copy it into your documents directory (on iOS) when you need to mutate it.
Where do the core data files live? in the bundle like my SQLite
database would?
Yes, they do. If you are using CD with a SQLite backing store, then it is just a SQLite DB file. (There is a special issue if you allow CD to store large BLOBs in the file system.)
With an update to the app what do I have to do to update the core data
files if they live outside my bundle?
I'm not sure what you are asking here? If you update your schema between versions, just as with SQLite, you will need to migrate your database to the new schema. CD provides some tools that work very well for additive migrations.
Good luck with your choice.
Andrew
Imagine an application which is supposed to work with different database vendors. As we all know the syntax for SQLs (especially DDL) is not portable. How do you deal with maintaing the SQL scripts?
Until now I see three options:
to store SQLs in format of one of the databases and have a tool which automatically converts from one syntax do another (do you know such tools?)
to store SQLs in some artificial language and a have a tool which is able to generate vendor-specific SQLs on demand (any recommendation here?)
to store SQLs in many database formats neglecting the redundancy (this is the worst one, isn't it?)
Do you recommend any of them? Do you have a better idea?
The development environment tries to follow the continuous integration principles, so automation is a key feature here.
Have a look at Liquibase (that's essentially your second item on the list)
http://www.liquibase.org
It's not perfect (e.g. it does not support check constraints) but it is quite useful
This video shows a solution using the Subsonic project http://subsonicproject.com/docs/Using_SimpleRepository and its data migration capabilities. The strategy is to use a general language and apply it to different databases.
Hope this is what you were looking for
Use some kind of ORM framework with schema generation capability.