Question

Ok where I work we have a fairly substantial number of systems written over the last couple of decades that we maintain.

The systems are diverse in that multiple operating systems (Linux, Solaris, Windows), Multiple Databases (Several Versions of oracle, sybase and mysql), and even multiple languages (C, C++, JSP, PHP, and a host of others) are used.

Each system is fairly autonomous, even at the cost of entering the same data into multiple systems.

Management recently decided that we should investigate what it will take to get all the systems happily talking to each other and sharing data.

Keep in mind that while we can make software changes to any of the individual systems, a complete rewrite of any one system (or more) is not something management is likely to entertain.

The first thought of several of the developers here was the straight forward: If system A needs data from system B it should just connect to system B's database and get it. Likewise if it needs to give B data it should just insert it into B's database.

Due to the mess of databases (and versions) used, other developers were of the opinion that we should have one new database, combining the tables from all the other systems to avoid having to juggle multiple connections. By doing this they hope that we might be able to consolidate some tables and get rid of the redundant data entry.

This is about the time I was brought in for my opinion on the whole mess.

The whole idea of using the database as a means of system communication smells funny to me. Business logic will have to be placed into multiple systems (if System A wants to add data to System B it better understand B's rules concerning the data before doing the insert), several systems will most likely have to do some form of database polling to find any changes to their data, continuing maintenance will be a headache, as any change to a database schema now propagates several systems.

My first thought was to take the time and write APIs/Services for the different systems, which once written could be easily used to pass/retrieve data back and forth. A lot of the other developers feel that is excessive and far more work than just using the database.

So what would be the best way to go about getting these systems to talk to each other?

Was it helpful?

Solution

Integrating disparate systems is my day job.

If I were you, I would go to great effort to avoid accessing System A's data from directly within System B. Updating System A's database from System B is extremely unwise. It is exactly the opposite of good practice to make your business logic so diffuse. You will end up regretting it.

The idea of the central database isn't necessarily bad ... but the amount of effort involved is probably within an order of magnitude of rewriting the systems from scratch. It is certainly not something I would attempt, at least in the form you describe. It can succeed, but it is much, much harder and it takes a lot more discipline than the point-to-point integration approach. It's funny to hear it suggested in the same breath as the 'cowboy' approach of just shoving data directly into other systems.

Overall your instincts seem pretty good. There are a couple of approaches. You mention one: implementing services. That's not a bad way to go, especially if you need updates in real time. The other is a separate integration application that is responsible for shuffling the data around. That's the approach I usually take, but usually because I can't change the systems I'm integrating to ask for the data it needs; I have to push the data in. In your case the services approach isn't a bad one.

One thing I would like to say that might not be obvious to someone coming to system integration for the first time is that every piece of data in your system should have a single, authoritative point of truth. If the data is duplicated (and it is duplicated), and the copies disagree with each other, the copy in the point of truth for that data must be taken to be correct. There is just no other way to integrate systems without having the complexity scream skyward at an exponential rate. Spaghetti integration is like spaghetti code, and it should be avoided at all costs.

Good luck.

EDIT:

Middleware addresses the problem of transport, but that is not the central problem in integration. If the systems are close enough together that one app can shove data directly in to another, they're probably close enough that a service offered by one can be called directly by another. I wouldn't recommend middleware in your case. You might get some benefit from it, but that would be outweighed by the increased complexity. You need to solve one problem at a time.

OTHER TIPS

Sounds like you may want to investigate Message Queuing and message-oriented middleware.

MSMQ and Java Message Service being examples.

It seems you are looking for opinions, so I will provide mine.

I agree with the other developers that writing an API for all the different systems is excessive. You would likely get it done faster and have much more control over it if you just take the other suggestion of creating a single database.

One of the challenges that you will have is to align the data in each of the different systems so that it can be integrated in the first place. It may be that each of the systems that you want to integrate holds entirely different sets of data but more likely it is data that is overlapping. Before diving into writing API:s (which is the route I would take as well given your description) I would recommend that you try and come up with a logical data model for the data that needs to be integrated. This data model will then help you leverage the data that you are having in the different systems and make it more useful to the other databases.

I would also highly recommend an iterative approach to the integration. With legacy systems there is so much uncertainty that trying to design and implement it all in one go is too risky. Start small and work your way to a reasonably integrated system. "Fully integrated" is hardly ever worth aiming for.

Directly interfacing via pushing/ poking databases exposes a lot of internal detail of one system to another. There are obvious disadvantages: upgrading one system can break the other. Moreover, there can be technical limitations in how one system can access the database of the other (consider how an application written in C on Unix will interact with a SQL Server 2005 database running on Windows 2003 Server).

The first thing you have to decide is the platform where the "master database" will reside, and the same for the middleware providing the much required glue. Instead of going towards API level middleware-integration (such as CORBA), I would suggest you to consider Message Oriented Middleware. MS Biztalk, Sun's eGate and Oracle's Fusion can be some of the options.

Your idea of a new database is a step in the right direction. You might like to read a little bit on Enterprise Entity Aggregation pattern.

A combination of "data integration" with a middleware is the way to go.

If you are going towards Middleware + Single Central Database strategy, you might want to consider achieving this in multiple phases. Here's a logical stepped process which can be considered:

  1. Implementation of services/APIs for different systems which expose the functionality for each system
  2. Implementation of Middleware which accesses these APIs and provides an interface to all the systems to access the data/services from other systems (accesses data from central source if available, else gets it from another system)
  3. Implementation of Central Database only, without data
  4. Implementation of Caching/Data-Storage Services at the Middleware level which can store/cache data in the central database whenever that data is accessed from any of the Systems e.g. IF System A's records 1-5 are fetched by System B through Middleware, the Middleware Data Caching Services can store these records in the centralized database and the next time these records will be fetched from the central database
  5. Data Cleansing can happen in Parallel
  6. You can also create a import mechanism to push data from multiple systems to the central database on a daily basis (automated or manual)

This way, the effort is distributed across multiple milestones and data is gradually stored in the central database on first-accessed-first-stored basis.

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