I am a new web developer and have some questions regarding MongoDB.
The site I am working on uses references that saved data locally with MongoDB. But after doing some research, I saw something called MongoDB Atlas, which saves data to a cloud. I guess my question is, if I were to host a website would it matter which one I chose to use? Or would I be restricted to Atlas? And why would someone pick one over the other?
MongoDb Atlas is a MongoDb server hosting provided by the same guys who make MongoDb (which means they typically know what they're doing). It's handy to use because everything is automatically configured for you, you get some dashboards, monitoring, backup, upgrades, etc. They have a free layer also (aka M0, it has some important restrictions though, read more at their site). As usual with Cloud offerings, they have good pricing for starters, but these can skyrocket if you're operating at significant scale.
If you choose to install MongoDb server "locally", you would need to configure the cluster yourself (althougth there are plenty of e.g. pre-configured MongoDb docker images out there), configure the backup, arrange monitoring, etc. A lot of work, if you want to do it properly.
Considering above, here is my advice...
Choose MongoDb Atlas when:
You have a small personal project
You're a startup and you believe that you will have tens of thousands users soon - Altas allows bootstrap things fast and for a relatively small cost
You're a medium sized company, you're fine with MongoDb pricing, and you don't expect to grow too much
Choose manual installation of MongoDb when:
You have a small single-server project that is not likely to grow into a multi-server deployment. You can run MongoDb docker in the same server - this is usually a bad practice in general, but it works fine for small workloads. I've used this setup (as part of Meteor Up deployment) and it worked fine with thousands of regular users (depends on your application's usage patterns though).
You're a Unicorn-level startup or bigger
You're building something for internal usage and have restriction of using cloud deployments
Your main servers are not located in the cloud. MongoDb cannot batch requests, so it is very important that your MongoDb server is located in the same datacenter as the backend servers, otherwise latency will kill your performance
Related
Could someone explain the benefits/issues with hosting a database in Kubernetes via a persistent volume claim combined with a storage volume over using an actual cloud database resource?
It's essentially a trade-off: convenience vs control. Take a concrete example: let's say you pay Amazon money to use Athena, which is really just a nicely packaged version of Facebook Presto which AWS kindly operates for you in exchange for $$$. You could run Presto on EKS yourself, but why would you.
Now, let's say you want to or need to use Apache Drill or Apache Impala. Amazon doesn't offer it. Nor does any of the other big public cloud providers at time of writing, as far as I know.
Another thought: what if you want to migrate off of AWS? Your data has gravity as well.
Could someone explain the benefits/issues with hosting a database in Kubernetes ... over using an actual cloud database resource?
As previous excellent answer noted:
It's essentially a trade-off: convenience vs control
In addition to previous example (Athena), take a look at RDS as well and see what you would need to handle yourself (why would you, as said already):
Automatic backups
Multizone deployments
Snapshots
Engine upgrades
Read replicas
and other bells and whistles that come with managed service opposed to self-hosted/managed one.
But there is more to it than just convenience/control that this post I trying to shed light onto:
Kubernetes is adding another layer of abstraction there (pods, services...), and depending on way of handling storage (persistent volumes) you can have two additional considerations:
Access speed (depending on your use case this can be negligent or show stopper).
Storage that you have at hand might not be optimized for relational database type of I/O (or restrict you to schedule pods efficiently). The very same reasons you are not advised to run db on NFS for example.
There are several recent conference talks on kubernetes pointing out that database is big no-no for kubernetes (although this is highly opinionated, we do run average load mysql and postgresql databases in k8s), and large load/fast I/O is somewhat challenge to get right on k8s as opposed to somebody already fine tuned everything for you in managed cloud solution.
In conclusion:
It is all about convenience, controls and capabilities.
Is it possible to run Google App Engine Development Server on my own server? How well development server datastore can handle high load and what amount of data will cripple it?
Some options for running an App Engine app without App Engine:
TyphoonAE, which runs Python apps using a stack of popular open-source components
appscale, which runs Python or Java apps off of Amazon's EC2 cloud
I haven't tried either. See this question for some additional discussion of both.
How well will the datastore perform if you simply spin up dev_appserver.py on a public IP? If you have a lot of data, poorly. When using the dev server, the entire datastore is held in memory, so as you insert data, Python's memory usage will climb. Once you've added enough data to cause your system to start swapping, your app will become unusably slow. There's an option in the dev server to use a SQLite datastore stub instead of the in-memory stub. This makes performance tolerable with large amounts of data, but it's not nearly as efficient as the production datastore, so datastore access is relatively slow even with small amounts of data. Certainly much slower than the in-memory datastore with small amounts of data.
Running the dev server as a stand-alone production server is just generally a bad idea. The API stubs provided with the dev server are designed for use by developers, not users. E.g. sending mail just writes a log entry instead of actually sending mail; logging in as an administrator entails clicking a checkbox that says "log in as administrator".
If you want to move an existing app off App Engine, use one of the options above. If you're developing an app from scratch, use Django or some other framework that's designed to run on generic hardware. The development server is intended for just that: development.
YES, with a lot of missing features (parallel queues, cron jobs, mail, XMPP,..), some hidden security issues, poor performance and stability, it is technically possible.
As you probably guessed, it's a bad idea.
Take for example the HTTP server; using the development server you would put in Production an undocumented BaseHTTPServer, quite impossible to configure and with probably some hidden security flaws ready to be exploited.
As #Drew well said, there are better choices out there to run you Google App Engine code in a Production ready environment that is not GAE.
Although this is 2y+ old thread, just adding my info: http://www.jboss.org/capedwarf
I am new to the area of web development and currently interviewing companies, the most favorite questions among what people ask is:
How do you scale your webserver if it
starts hitting a million queries?
What would you do if you have just one
database instance running at that
time? how do you manage that?
These questions are really interesting and I would like to learn about them.
Please pour in your suggestions / practices (that you follow) for such scenarios
Thank you
How to scale:
Identify your bottlenecks.
Identify the correct solution for the problem.
Check to see you you can implement the correct solution.
Identify alternate solution and check
Typical Scaling Options:
Vertical Scaling (bigger, faster server hardware)
Load balancing
Split tiers/components out onto more/other hardware
Offload work through caching/cdn
Database Scaling Options:
Vertical Scaling (bigger, faster server hardware)
Replication (active or passive)
Clustering (if DBMS supports it)
Sharding
At the most basic level, scaling web servers consists of writing your app in such a way that it can run on > 1 machine, and throwing more machines at the problem. No matter how much you tune them, the eventual scaling will involve a farm of web servers.
The database issue is way more sticky to deal with. What is your read / write percentage? What kind of application is this? OLTP? OLAP? Social Media? What is the database? How do we add more servers to handle the load? Do we partition our data across multiple dbs? Or replicate all changes to loads of slaves?
Your questions call more questions, i.e. in an interview, if someone just "has the answer" to a generic question like you've posted, then they only know one way of doing things, and that way may or may not be the best one.
There are a few approaches I'd take to the first question:
Are there hardware upgrades that may get things up enough to handle the million queries in a short time? If so, this is likely an initial point to investigate.
Are there software changes that could be made to optimize the performance of the server? I know IIS has a ton of different settings that could be used to improve performance to some extent.
Consider going into a web farm situation rather than use a single server. I actually did have a situation where I worked once where we did have millions of hits a minute and it was thrashing our web servers rather badly and taking down a number of sites. Our solution was to change the load balancer so that a few of the servers served up the site that would thrash the servers so that other servers could keep the other sites up as this was in the fall and in retail this is your big quarter. While some would start here, I'd likely come here last as this can be opening a bit can of worms compared to the other two options.
As for the database instance, it would be a similar set of options to my mind though I may do the multi-server option first as redundancy may be an important side benefit here that I'm not sure it is as easy with a web server. I may be way off, but that is how I'd initially tackle this.
Use a caching proxy
If you serve identical pages to all visitors (say, a news site) you can reduce load by an order of magnitude by caching generated content with a caching proxy such as Varnish or Apache Traffic Server.
The proxy will sit between your server and your visitors. If you get 10,000 hits to your front page it will only have to be generated once, the proxy will send the same response to the other 9999 visitors without asking your app server again.
probably before developer starting to develop the system,
they will consider the specification of the server
maybe you can decrease use of SEO and block it from search engine to craw it
(which is the task that taking a lot of resource)
try to index everything well and avoid to making search easily
Deploy it on the cloud, make sure your web server and webapp cloud ready and can scale across different nodes. I recommend cherokee web server (very easy to load balance across different servers, and benchmarks proves faster than Apache,). For ex, google cloud (appspot) needs your web app to be Python or Java
Use caching proxy eg. Nginx.
For database use memcache on some queries which are suppose to be repeated.
If the company wants data to be private , build a private cloud , Here , Ubuntu is doing very good job at it fully free and opensource : http://www.ubuntu.com/cloud/private
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[An Updated List 21st Aug 09]
Help me Compile a List of all the Advantages & Disadvantages of Building an Application on the Google App Engine
Pros:
No need to buy servers or server space (no maintenance).
Makes solving the problem of scaling easier.
Free up to a certain level of consumed resources.
Cons:
Locked into Google App Engine ?
Developers have read-only access to the filesystem on App Engine.
App Engine can only execute code called from an HTTP request (except for scheduled background tasks).
Users may upload arbitrary Python modules, but only if they are pure-Python; C and Pyrex modules are not supported.
App Engine limits the maximum rows returned from an entity get to 1000 rows per Datastore call. (Update - App Engine now supports cursors for accessing larger queries)
Java applications may only use a subset (The JRE Class White List) of the classes from the JRE standard edition.
Java applications cannot create new threads.
Known Issues!! : http://code.google.com/p/googleappengine/issues/list
Hard limits
Apps per developer - 10
Time per request - 30 sec
Files per app - 3,000
HTTP response size - 10 MB
Datastore item size - 1 MB
Application code size - 150 MB
Update Blob store now allows storage of files up to 50MB
Pro or Con?
App Engine's infrastructure removes many of the system administration and development challenges of building applications to scale to millions of hits. Google handles deploying code to a cluster, monitoring, failover, and launching application instances as necessary.
While other services let users install and configure nearly any *NIX compatible software, App Engine requires developers to use Python or Java as the programming language and a limited set of APIs. Current APIs allow storing and retrieving data from a BigTable non-relational database; making HTTP requests; sending e-mail; manipulating images; and caching. Most existing Web applications can't run on App Engine without modification, because they require a relational database.
Pros:
Scalable
Easy and cheaper (in short term).
Nice option for start-ups/individuals.
Suitable for apps that just store and retrieve data.
Cons:
Not suitable for CPU intensive calculations. They are slower and expensive.
Scalability doesn't matter much cuz if an app works at Google scale then probably it makes enough money to run on its own servers.
They have lots of limitations thrown here and there, as a result deep data analysis is difficult. Like you cannot produce a social graph using GAE.
I would say its not meant for serious businesses and expensive in long run.
(A huge new) PRO: GAE now supports MySQL :
https://developers.google.com/cloud-sql/
Pros:
built-in ui for unified logs
built-in web interface for task queues
built-in indexes on list of primary objects.
Cons:
loose logs very fast
VERY expensive
VERY expensive
VERY expensive
Un-hackable. Scales because you're obligated to code in a way that scales.
Longer development cycles. Sometimes you just want to hack something together and throw it away after 5 hors. With appengine you have to proper code it and write a lot of stuff to make it sure it scales. You can't just do a "find . | grep .avi | xargs ffmpeg -compress ...." :)
You will loose hours trying to do the simplest tasks like sending push notifications to APNS (iPhone). Although it's fine if you only want to support android in the future.
Terrible to make cleanups on the database. It's a HUGE pain in the ass to fix rows in the database, mainly because terribly slow, but it also requires a lot of code to loop properly within it's time constraints.
It was a pain to port Lucene to work on it's "filesystem".
Slow for what you pay.
Even MORE expensive if your app has spikes of traffic. My app has those spikes if a user that has many followers makes an action and we have to push notifications to his followers. Because of that I have to keep 10 inactive servers always on ($$$$$) to handle spikes.
Appengine isn't too bad due to the fact that I have the option to burn $$$$ instead of being concerned about scalability and fixing bottlenecks to reduce server usage. Sometimes it worth it.
My advice to people starting new products is to go with hetzner.de which is where I host my other products servers. It's cheap and extremely hackable. I have one server at hetzner that is handling 3x more traffic than the product that I have on appengine. The difference in price is $100 a month versions $2700 a month!
I have system admin experience, so the bottom line is that I would never choose appengine over having my own ROOT server. Don't be that bored software engineer wanting to experiment new things instead of building great products!
Pro: Unlimited scalabity to your application and scales with demand.
Con: Not available in some countries (Argentina).
Edit
Available worldwide, but only through Google Groups for App Engine.
When assessing pros and cons, I think it is important to clarify the market for which one is representing. Developers looking for a cost-effective solution to help them with the steep part of their planned hockey-stick growth curve will weigh heavily the cons already listed. For a small business owner, however, GAE is a God-send. These folks most often are looking to "the cloud" as a means to more effectively run their business (i.e. sell physical product and services). For the SMB, GAE the pros already listed can be much more valuable compared to the hockey-stick seeking dev, whilst the cons weight in at a fraction of the devs' measure. I don't see the GAE team doing anything related to SMB positioning, so I guess answers like this are me just pulling on Superman's cape, and spitting into the wind. Really GAE should be absolutely ruling the SMB space now. If not (I have no insights re: user base), then its is a greatly lamentable failure.
I believe , GAE is yet to mature in terms of providing the basic features for serious business such as Datastore with complex primary key, java.awt.* support, these are just a few I'm naming.
Other than the free space and to build some "Hobby" websites, I strongly feel GAE is NOT the place java guys should looking into.
I'm having applications built on the JSP/Servlets and MySQL, thinking about migrating to GAE, but I find I will be spending more "value time" on the migration than just buying a space from some java hosting provider such as EATJ, etc (Sorry not marketing, just an experience).
Another big issue I've got is migration of my existing mySQL data into GAE, bulkupload is really pathetic and has no client support.
No support for Local Db to Server DB upload.
Once the GAE is ready with "all the Cons" mentioned by above, then I'll think we can look in to this migration.
You are force to own a cell phone line, and your country+carrier must be able to receive international SMSs.
(I hate cell phones, and my mom's or co-workers won't get the SMSs)
Con: No Other RDBMS or NoSQL databases are not possible ....
Con: All your base are belong to us
... On a serious note:
Con: You don't control the environment your application runs in. The same cons as with outsourcing any component. Fun for toys, not for business (yet) IMHO.
Various things like API for Google proprietary backends such as their database system and other 'lockdowns' and frameworks that mean your code is tied, in some loose sense to their system can create cost issues later if you want to migrate from GAE. Of course, you could abstract these.
I like GAE, AppJet and others. They are cool. But everything has its place. If you want freedom and the ability to control your language's modules, API, syntax/stdlib versions and whatnot ... don't relinquish control to a service provider.
The lack of standards for environments and specifications for what your app can expect worries me in the cloud arena.
common sense stuff really.
Con: Limited to Java and Python
In a corporate development environment writing mostly administrative software, should every developer use their own database instance, or should they use a central database instance during development? What are the advantages and disadvantages of each approach? What about other environments and other products?
If you all share the same database, you might have some issues if someone make a structure change to the database and that the code is not "Synchronized" with it.
I highly recommend one DB per developer for the only reason that you don't want to do "write" test to see someone else override you right after. A simple exemple? You try to display product for a website. Everything works until all the products disappear. Problem? Another developer decided to play with the "Active" flag of the product to test something else. In cases like that, a transaction might not even work. End of the story, you spend time debugging for someone else action.
I highly recommend replicating the staging database to the developer database once in a while to synchronize the structure (or better, have a tool to rebuild a database from scratch).
Of course, we require scripts for changes to the database and EVERYTHING is in a Source Control.
The days when database environments should be scarce are long gone. I'm writing this posting on a XW9300 with 5x15k SCSI disks in it. This machine will run a substantial ETL job in a fairly reasonable length of time and (in mid-2007) cost me about £1,700 on ebay including the disks. From a developer's perspective, especially on database centric projects like data warehousing, the line between a developer and a DBA is quite blurred. As I write this I am building a partition management framework for a SQL Server 2005 data warehouse.
Developers should have one or more development databases of their own for (IMO) these reasons:
Requires people to keep stored procedures, patch scripts and schema definition files in source control. Applying the patches can be automated to a fairly large extent. There are even tools such as Redgate SQL Compare Pro that do much of the grunt work for this.
Encourages an application architecture that facilitates easy configuration management and deployment, as people have to deploy onto their own workstations. Many deployment wrinkles will get sorted out long before they hit production or people even realise they could have gone wrong.
Avoids developers tripping up on each other's work. On something like a data warehouse where people are working with ETL code this is an even bigger win.
It encourages a degree of responsibility as developers have to learn basic database administration. This also eliminates a lot of the requirements for operational support staff and some of the dev-vs. ops friction.
If you have your own database, there are no gatekeepers obstructing experimentation or other work on it. The politics around managing 'servers' disappear as there are no 'servers'.
This is a productivity win in an any environment with significant incumbent bureaucracy.
For small data volumes an ordinary PC is fast enough for this. Developer editions or licencing are available for most if not all database management systems and will run on a desktop O/S. If you're working with Linux or Unix this is even less of an issue. For larger data volumes, up to and including most MIS applications, a workstation like an HP XW9400 or Lenovo D10 can be outfitted with 5 15k disks for less than the cost of a lot of professional development tooling. (Yes, I know it's dual licence, but a commercial all-platform licence for QT is about £4000 a seat).
A machine like this will run an ETL process with 10's to 100's of millions of rows faster than you might think.
It facilitates setting up more than one environment for smoke testing or reconciliation purposes. As you have complete control over the machine, you have quite a lot of scope for mocking up conditions in a production environment. For example, I once made a simple emulator for Control-M by just bodging some of its runtime scripts.
Where you have this level of control and transparency over the environment you can produce a fairly robustly tested deployment process which does quite a lot to eliminate opportunities for finger-pointing in production deployment.
I've seen small teams working with 14 environments, and had 7 active on a workstation at the same time. On database heavy work such as ETL, where you're with with whole tables, working in a single dev environment is a recipe for time wastage or spending your time walking on eggshells.
Also, you can use single user development licences for database platforms, which can save you the cost of the workstations just in database licencing. Most developer licences (Microsoft and OTN are a couple of examples I'm familiar with) will let you use the system on a single workstation for a single developer free or for a nominal price.
Conversely, licencing terms on shared development servers are often somewhat murky and I've seen vendors try to shake customers down for licencing on dev servers on more than one occasion.
Each of our developers has a fully functional database. Changes are scripted and source controlled like any other code.
Ideally, yes, each developer should have a "sandbox" development environment, so they can test their code even before deploying it to a shared testing/staging environment.
Each developer's environment should run scripted tests that reset the database to a known state. This is impossible to do in a shared environment.
The cost of giving each developer their own instance is less than the cost of the chaos resulting from multiple developers trying to test volatile changes together in a shared environment.
On the other hand, in many IT shops the system uses complex infrastructure, involving multiple application servers or multiple physical nodes. Then the economics change; it's less expensive for people to cooperate and avoid stepping on each other's work than it would be to replicate it for each developer. Especially true if you integrate expensive third-party systems that don't give you licenses for multiple development environments.
So the answer is yes and no. :-) Do give each developer their own environment if that environment can be reproduced inexpensively.
My recommendation is to have 2 levels of development environment:
Each developer has their own personal development system, with its own dp, web servers, etc. This allows them to code against a known setup, write automated (system level) tests that initialize their database and systems to a known state, etc.
The development integration environment is shared by all developers and used to make sure everything is working together as expected before handing it off to QA. Code is checked out from source control and installed there, and there's only a single instance of any servers (db or otherwise).
This question hints at what a developer needs to do his/her job. Certainly a private DB instance should be provided. Equally important, I would make sure that the DB is the same product/version as what you intend to deploy to. Don't develop on MySQL 6.x and deploy to MySQL 5.x. (This goes for app servers, and web servers as well!)
Having a developer DB doesn't necessarily ean you need it hosted on your local machine. You could have a central DBMS host machine with all dev dbs located on it. The pros are the garauntee that you develop against the target DB. Less overhead on dev boxes, more space/horsepower for beefy IDEs and app servers. The cons are single point of failure for all devs. (The DBMS server goes down nobody can work.) Lack of dev exposure to setting up and administering the DBMS. Devs cannot experiment as easily with upcoming DB releases or alternate DB choices to solve tough problems.
Some of the pros can be cons and vice-versa depending on your organization and structure. Maybe you don't want devs administering the DBMS. Maybe you do plan to support varying DB platforms. The decision boils down to your organization as well as your target platform choices. If you plan to target a variety of DB/OS/app server combinations then each dev should not only have their own DB but should work in a unique combination. (MySQL/Tomcat/OSX for one DB2/Jetty/Linux for another Postegres/Geronimo/WinXP for a 3rd, etc.) If you setup an ASP (Application Service Provider) type shop on an iSeries on the other hand then of course you'll likely have a central host with all dev dbmses still each dev should have at least a separate db instance to allow structural changes to schema.
I have an instance of SQLServer Development Edition installed locally. We have a QA DB server, as well as multiple production servers. All development and integration testing is done using my local server (or other developers local servers). New releases are staged to the QA server. Each release, after acceptance by the customer, is put into production.
Since I mostly do web development, I use the web server bundled with VS2008 for development and local test, then publish the web app to a QA web server hosted on a VM. Once accepted by the customer, it is published to one of several different production web servers -- some virtual, some not, depending on the application.
My department at my company only has limited development environments, purely because of cost of support and hardware. We have a couple of environments which are based on t-1 nightly refreshes from production, and some static ones.
Ideally, everyone should have their own, but in many cases, this is going to be impractical when the following are true:
you have a large number of developers needing resources (our department has maybe 80)
each developer needs multiple resources (typically i use 4-5 different dbs each day)
up to date data is important (you just cant refresh them fast enough)
In these cases, shared instances and good communication are whats needed.
One advantage to one database per developer, each developer has a snapshot of their own data in a "known" state.
I like the idea of using a local version when a developer must be isolated - developing a schema change, performance testing, setting up specific scenarios, etc...
At other times use the shared version as to insure everything is in sync with each other.
I think there's a terminology problem here. It's been a while since I've worn my DBA hat (golly gee, almost 10 years) - so someone else can chime in and correct me.
I think everyone is in agreement that each developer should have his own sandbox schema set.
In MySQL and Sybase/MS SQLServer, each database engine can support multiple databases. Each database is (normally) fully independent of the other database. So you can have one database engine instance, and give each developer his database space to do as he wish. the only problem is if the developers are using tempdb -- there can be collisions there (I think -- this you will need to look up). Just be careful that cross-database queries with fixed database names are not used.
In Oracle, the database engine instance is tied to a particular schema set. If you have multiple developers on the same engine, they are all pointing to the same tables. In this case, yes, you will need to run multiple instances.
Each of our developers has a local database. We store the create script AND a dump of the "standard data" in our SVN repo. We have an extensive set of tests that must pass against this test data. We also have a "sandbox" database that is available for people to put data in that they want shared into the standard data. This works well for us and allows us to let developers modify their local copies of data to test things, but we control what gets passed to other developers. We also strictly control schema changes, so we don't encounter the problems that someone else mentioned.
It really depends on the nature of your application. If yours is a client-server architecture in a distributed environment, it is best to have a central database that everyone uses. If the product gives users an environment with local database instances, you can use that. It is best if your development mirrors the real world environment as closely as possible.
It is also dependent on what stage of development you are in. Probably in the early stages, you dont want to get bogged down by connectivity, network and distributed environment issues and just want to be up and running. In such a case, you can start with a database instance-per-user model before switching to the central model as the product reaches some level of maturity.
In my company we tend to copy the entire DB when working on non-trivial new features. The reasoning there is disk space is cheap, whereas accidental data loss (even if it's test data) isn't.
I've worked in both types of development environments. Personally, I prefer to have my own DB/app server. However, there may be some advantages to using a shared infrastructure for development.
The main one is that a shared environment more closely resembles a real-world scenario: you are more likely to uncover problems with locking or transactions when all developers share a DB. Giving each developer their own DB may lead to "it works on my DB" syndrome.
However, if you need to apply and test schema changes or optimisations, then I can see problems in this sort of set-up.
Maybe a compromise solution would work best: all developers share infrastructure, and if someone needs to test schema changes, they create their own temporary DB instance (maybe there is one just sitting there for this purpose?) until they are happy to commit the new schema to source control.
You do have your entire schema (and test data) in source control, right? Right???
I like the compromise solution (all developers share infrastructure, and if someone needs to test schema changes, they create their own temporary DB instance (maybe there is one just sitting there for this purpose?) until they are happy to commit the new schema to source control.)
One DB per developer. No question. But the issue really is how to script entire databases, "control data", and version them. My solution is here : http://dbsourcetools.codeplex.com/
Have fun. - Nathan.
The database schemas should be held in source control and developers should own the changesets checked in for code and db together. Prior to checkin the developer should be working on his own database. After checkin, an automated build (eg: on checkin, nightly, etc), should update a central integrated db, along with the apps themselves.
At developer instance level the data loaded should be appropriate for unit testing, at least. At integrated level, the shared db should hold data also appropriate for testing, but should not rely on production replication - this is just a slack substitute for managed test data.
In my experience the only reason that developers opt for a shared db is that they believe that developing and running on recent production data is somehow 'real' and means that they can put less effort into testing. They prefer to tread on each others toes and put up with a shared db that slowly corrupts before the next production refresh than write and manage proper tests. It's this kind of management practice that gives the IT world the poor reputation to deliver that it currently has.
I'd suggest to use one instance of the database. You don't want your database to be a moving target.