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I'm building a web application right now for my company and for whatever reason, can't get mySQL working on my Mac w/ my Ruby install (OSX 10.5). SQLite works fine though, so would it be a problem to use SQLite for now so I can get to work on this and then just change up my database.yml file to point to a mySQL database when I deploy (assuming I rerun migrations and such)?
Also, what are the benefits/drawbacks of using mySQL over SQLite in a RoR application? I've always used mySQL by default in the past, but never learned SQL directly (always through ActiveRecord) and never thought too much about the difference.
Benefits of MySQL/PostrgreSQL/etc
Pros
Stronger data typing, which means cleaner data
Ability to store more data
Scale better to larger data sets
Spatial support (think GPS)
Full Text Search (FTS)
Cons
Stronger data typing means data will be validated, bad data will cause errors
Not a good candidate (if even possible) for devices with limited resources (iPhone, Blackberry, iPad, etc)
I would pick PostgreSQL v8.4+ over MySQL given the choice. MySQL's features lag behind the rest of the major SQL database alternatives.
THe biggest performance issue you may run into is table locks. SQLite unfortunately does not have row level locking. So if your app is going to run multiple processes / threads (as with multiple web users) its likely some threads will not be able to perform an SQL op. For this reason i would go with MySQL - or perhaps Postgresql.
Should be no problems, as MySQL should have a superset of SQLite capabilities, and as #Sean pointed out, performance should only increase. Just try to make sure you're not using anything too SQLite specific (I'm mainly a SQL Server and Oracle guy, so don't know what that would be, if anything). Remember, the "S" in SQL stands for Structured, not Standard ;)
Paul.
SQLite is perfect for a desktop or smartphone application ("embedded" usage). However, if you plan to build a web-application, you are highly encouraged to make use of a non-embedded DMS like MySQL. The benefits are countless, such as 3rd party design and analysis apps, performance etc ...
Every single book that teaches programming (or almost anything else) starts off with a whole bunch of spiel on why what it's about (C++, MySQL, waterskiing, skydiving, dentistry, whatever) is the greatest thing in the world. So I open the MySQL O'Reilly book, and read the intro, and get the traditional sermon. The main points that the book mentioned were:
MySQL has been shown to have tied Oracle as the fastest and most scalable database software.
It's free and open source.
Sounds pretty convincing, but I know there's always at least two sides of every story. I knew I needed to be disillusioned when I saw someone suggest to someone to use Oracle instead of MySQL and thought, "Why in the world would you want to do that?!", just because of the few paragraphs I'd read, with no other justification. So lets investigate the other side of the story:
What are some reasons NOT to use MySQL?
Here's just a random list of stuff that popped into my head. It's CW, so feel free to add to it as necessary.
Oracle provides a top notch ERP built on their database. If your company is subject to Sarbanes-Oxley regulations, this is quite a bit above "crucial."
SQL Server licenses come with Analysis Services, Integration Services, and Reporting Services. If you want to do anything with OLAP, ETL, or reporting, these three are great applications that are built on the SQL Server stack.
SQL Server has native .NET data types (in 2008). Absolutely brilliant for .NET shops dealing with geospatial datasets.
MySQL does not support check constraints.
SQL Server includes the over clause, which helps when dealing with the "top n rows in each group" problem. Essentially, you can do aggregate functions partitioned over the dataset any way you'd like.
SQL Server uses Kerberos and Windows authentication natively. MySQL does not tie into Active Directory.
Superior performance on subqueries (almost any database has subquery performance that is superior to MySQL's)
Oracle, SQL Server, PostgreSQL and others have a richer set of join algorithms available to them; this means joins can often be performed faster, especially when large tables are involved.
MySQL has been shown to have tied oracle as the fastest and most scalable database software.
Making that statement about any two database systems is probably enough to throw the book away without reading the rest. Database systems are not commodities that can be compared with a couple lines of information, and will not be for the foreseeable future.
One reason that the statement is obviously false is that MySQL has very limited plan choices available. For instance, MySQL can't use merge join or hash join -- two fundamental algorithms that have useful performance characteristics. That's pretty much the end of the story for many query workloads. It is trivial to show a reasonable query that is orders of magnitude faster with a merge join.
There are plenty of other criticisms of MySQL versus XYZ and vice-versa. My point is that this is a complex issue, and the book is drastically oversimplifying. If you're getting involved in databases at all, you need to spend time diversifying your knowledge and understanding fundamentals.
My personal opinion is that MySQL and SQLite are the worst places to start. Pick something like Oracle (which can be downloaded free of charge for learning/evaluation, which many don't realize), PostgreSQL (BSD license), or MS SQL. FirebirdSQL might be good, too. Once you familiarize yourself with a few systems, you'll be able to make an informed choice about whether the trade-offs MySQL makes are right for you.
Everyone seems to be missing one of the main reasons to stick with Oracle/MS. You've already got a stable full of DBAs that know those products inside and out.
The default collation in mysql is case-insensitive. This is not a problem per se, but I think this strange default is an indication that it was targeted at hobby-developers, rather than professionals. This is a big assumption, but I'd think any professional would expect a database to compare strings for identity by default (i.e. using a binary collation).
Manipulation of tables during transactions causes implicit COMMITs. While this might not look grieve at the first glance, you will notice that you cannot cannot work under ACID conditions if altering/creating tables is an inherent part of your application.
MySQL can certainly match or beat Oracle in speed. I've done it numerous times myself. Ok, so I had to use various table types like black hole, merge, innodb, and myisam in just the right laces. And it took me a few days to get everything working just right. The Oracle DBA got things working in an hour or two.
MySQL is fine for 98% of the sites out there, maybe more. But it is fairly easy to bring it to a crawl without a lot of data if you don't know what you are doing. Oracle is quite a bit harder to bring to a crawl, but it can still be done. I've worked with both with datasets in the hundreds of millions of records (tiny by some measures). MySQL takes quite a bit more attention.
No database can scale indefinitely, which is why nosql "databases" are becoming so popular. I think the real question is if MySQL is "good enough" for what you need to do. The price is certainly right. The same could be said about PHP.
Why does Facebook use MySQL? Could you imagine what it would cost them to buy enough Oracle licenses!? It's good enough.
The future is of sun (the company behind mysql) is unclear and you don't know whether there will be a company to back the product.
MySQL is very tolerant of ambiguities -- something you don't want in a database system. Here are a few examples off the top of my head:
As another poster stated, CHAR and VARCHAR columns are case-insensitive, already a pretty bad sign.
You can INSERT into a table that has a column without a default value that is also NOT NULL. Yes, really! Instead of throwing an error, MySQL will pick a value for you based on the data type, e.g. 0 for numbers.
You can use a GROUP BY statement while some columns are neither using an aggregate function, nor included in the GROUP BY statement. The outcome is pretty much random. No warnings or errors here either, in my experience.
MySQL is also far from rock-solid. Just this month, I discovered a bug in the (admittedly old, but a "stable release") version of MySQL used by DreamHost that results in data loss. (Certain conditions when creating a table with variable-length rows.)
I've been using MySQL for many years and still do, but would never dream of using it for anything serious, where data loss would be a big problem. It's great for non-mission-critical web sites and blogs though.
I knew I needed to be disillusioned
when I saw someone suggest to someone
to use oracle instead of MySQL and
thought, "Why in the world would you
want to do that?!"
Because your company has been using Oracle for the past ten years, or because you equate enterprise usage with 'must be good' and open-source with 'free crap'. That's just about the only reason. Everyone I know who has worked with Oracle loathes it. Everyone I know who has worked with MySQL, assuming they don't love it, at least consider it a better alternative to Oracle in almost every regard.
SQL RMDBs are so complex though, that in almost every respect there's something one DB does that another doesn't. It is also, unfortunately, a fact of comparing databases that people quote statistics without using properly configured servers. If you have two default configurations for a server, one might be better than the other, but that's about as far as the comparisons usually go. They don't reflect the fact that these gigantic applications have a million little switches and toggles you can use to speed certain things up, increase reliability and generally screw up bad science.
MySQL tends to be a very general purpose database system, you can use it for almost anything that you'd use Oracle, SQL Server, PostgreSQL, DB2, etc for.
However, these different systems have different strengths, PostgreSQL has a ton more functionality than MySQL and can handle some very specific tasks that MySQL struggles with. SQL Server usually integrates with Microsoft products very easily whereas MySQL you'd have to do some extra work to make them play together. Oracle is MASSIVE, they're not just databases and when you're dealing with large, expansive systems Oracle probably has the gear to cover everything under the 1 roof, whereas you'd need to tie a bunch of disparate systems together to have MySQL has your database system.
Whether or not to use MySQL should be based upon whether or not it is reasonable to use MySQL.
Disclaimer: I have been using MySQL since 2001 and still love it, but here are a few reasons that make me doubt about my fidelity...
There are some false arguments (it was true a few years ago) in some of the answers I read. Before making a choice, check MySQL documentation and its up-to-date list of features. You could be surprised.
Each DB server lack functionalities. This is not a real blocking issue if you do not specifically need them.
For me, the main issues are elsewhere:
The time needed to have a bug fixed and published in a stable release. It is a shame. (For some bugs... it takes years (no kidding)!)
The frequency of stable releases.
But since this year, the new issues are:
The number of increasing branches (Percona, Google, Facebook, etc.).
Sun is unclear with his strategy.
Many MySQL employees left the company.
It's free and open source.
True. But keep in mind that MySQL is, in many cases, not free for commercial use. MySQL and the connectors (the official drivers for various languages), are GPL licensed.
If you use, say, the Connector/.NET to connect to MySQL your code have to be GPL compatible. It's dual licensed though, so you can buy an enterprise version under another license - and I believe they have a (either free or just very cheap) program that lets you license the connectors under a different license.
Everyone I know using MySQL is unaware of this :-)
Basically, there are several choices for a database. Frankly, in today's world, DB choice is less important than it was a few years ago. Here are a few issues to consider.
Most of the current database systems in widespread use such as SQL Server (and SQL Server Express), Oracle, MySQL, SQLLite, etc. are relatively standards compliant and can be used somewhat interchangeably. Some serve different niche markets. For example, SQL Server, MySQL, and Oracle are all good choices for large Enterprise applications. SQLLite is very good for applications which deploy on a client and need a local database with a small footprint and minimal configuration. (In my opinion, Oracle is extremely over-priced, is backed by an arrogant unresponsive company. It would never be my first choice on any project. I would only use it if it was mandated by the client or by necessity.)
A high percentage of top-end developers are using tools such as Hibernate(Java)/NHibernate(.NET) to build their data access layers. Hibernate variants strongly encourage developers to start with development of the object model rather than the database model. The Hibernate application then generates the data model automatically--and even handles data model updates. Hibernate variants can be used with any of the major database vendors. Changing your database choice can be as simple and painless as selecting a different database type in your configuration. On a side note, I should mention that while Hibernate and NHibernate are cross-database-compatible, they do not work on the lowest common denominator. The data access code in these applications is often designed to take advantages of special features within a given database engine. For example NHibernate supports access to the NVarchar(Max) data type in SQL Server which allows for very long strings.
In most applications, issues with database performance do not derive directly from the speed of reads and writes. Most of the issues relate to how the application manages the caching of frequently accessed data. For example, in online blog site, it makes sense to cache blog posts once they have been read so they are not repeatedly fetched from the database. This caching mechanism is almost always primarily handled by the application code rather than database server--though database servers do provide some caching. Hibernate/NHibernate have excellent caching support built in as does Microsoft's ASP.NET and their new MVC framework built on top of ASP.NET.
Enterpise databases (SQL Server, Oracle, MySQL) are best for situations where functionality such as replication, clustering, huge datasets, etc. are required.
I don't like MySQL licence : Firebird and PostgreSQL are better
There is no real hotbackup include in the MySQL by Sun
you can also look here which is interresting link and comment !
MySQL is free, but it takes an expert to maintain. Someone who naturally uses the command prompt and is not afraid to experiment. In some cases, MySQL problems are too complex, and the right people to troubleshoot them may not be available for any amount of money.
SQL Server is priced in the middle range. It can be maintained by "normal people", the kind who go home every day on 17:00 and have a natural disinclination to fifty page HOW-TO's. SQL Sever performs well in most instances but can break down in specific scenarios.
Oracle is the most expensive and requires highly paid operators. If you have the money, Oracle is a "safe" choice, because there's nothing Oracle won't do for money.
Three products, three markets!
A couple of pages listing gotchas (such as this and this) make me want to stay as far away from MySQL as possible. Here's a more neutral comparison of Postgres and MySQL.
As for the open source aspect others mentioned: MySQL is open source and free, only if your application is, too. If it's not, you need a commercial license.
My personal story:
Adding a new index to a table of about 10k rows.
MySQL side
about 30 seconds.
Postgres side
about 1 second.
I've worked with MySQL for years, and SQL Server only over the past year. I don't really see one being any easier or harder to use than the other in most cases. I do wish, however, that MSSQL had some of the features that MySQL possesses (e.g. being able to insert multiple rows on a single INSERT statement).
Also, if you don't have to use RDBMS, checkout redis. It is basically memchached with persistence with asynchronous write through. The performance is not on the same scale with MySQL.
Well... I guess the comparison isn't really fair to MySQL since it's not RDBMS...
I am developing a Rails application that will access a lot of RSS feeds or crawl sites for data (mostly news). It will be something like Google News but with a different approach, so I'll store a lot of news (or news summaries), classify them in different categories and use ranking and recommendation techniques.
Should I go with MySQL?
Is it worthwhile using IBM DB2
purexml to store the doucuments?
Also Ruby search implementations
(Ferret, Ultrasphinx and others) are
not needed If I choose DB2. Is that correct?
What are the advantages of
PostreSQL in this?
Does it makes sense to use Couch DB in
this scenario?
I'd like to choose the best option but without over-complicating the solution. So I discarded the idea to use two different storage solutions (one for the news documents and other for the rest of the data). I'm also considering only "free" options, so I didn't look at Oracle or MS SQL Server.
purexml is heavier than SQL, so you pay more for your roundtrip between webserver and DB. If you plan to have lots of users, I'd avoid it, your better off letting your webserver cache the requests, thus avoiding creating xml(rss) everytime, if that is what you are thinking about.
I'd go with MySQL because its really good at serving and its totally free, well PostgreSQL is too, but haven't used it so I can't say.
CouchDB could make sense, but not if you plan on doing OLAP (Offline Analysis) of your data, a normal RDBMS will be better at it.
Admitting firstly that I generally don't like mysql, I will say that there has been writing on this topic regarding postgres:
http://oldmoe.blogspot.com/2008/08/101-reasons-why-postgresql-is-better.html
This is always my choice when I need a pure relational database. I don't know whether a document database would be more appropriate for your application without knowing more about it. It does sound like it's something you should at least investigate.
MySQL is probably one of the best options out there; light, easy to install and maintain, multiplatform and free. On top of that there are some good free client tools.
Something to think about; because of the nature of your system you will probably have some tables that will grow quite a lot very quickly so you might want to think about performance.
Thus, MySQL supports vertical partitioning but only from V 5.1.
It sounds to me the application you will build can easily become a large-scale web app. I would suggest PostgreSQL, for it has been known for its reliability.
You can check out the following link -- Bob Ippolito from MochiMedia tells us why they ditched MySQL for PostgreSQL. Although the posts are more than 3 years old, the issues MySQL 5.1 has recently tend to prove that they are still relevant.
http://bob.pythonmac.org/archives/category/sql/mysql/
MySQL is good in production. I haven't used PostgreSQL for rails, but it's a good solution as well.
In the dev and test environments I'd start out with SQLite (default), and perhaps migrate to your target DB in the test environment as you move closer to completion.
Is there any formal performance and stress test reports of open source database, specially sqlite,MySQL an PgSQL?
I want to use sqlite in server for its simple structure and easy embeddable capability. But I can not find any pros and cons (by Googling and Yahoo!ing) regarding performance of these database software.
Please suggest.
I found this article. It has a disclaimer at the top about the age of the information. However, it may be some help to you.
Here is another article that seems a little more recent and up2date.
Seems from reading these that SQLite is quite adequate in terms of performance.
Sysbench is a great utility for benchmarking mysql and I believe has plugins or the capability to test PostgreSQL. Keep in mind that you're not going to get a simple number that says "DBMS A is faster than DBMS B" -- at best you can hope to get an idea of what kind of scaling you'll get for a particular type of workload that is hopefully similar to whatever workload you'll end up throwing at your system.
Regardless of performance, if you really know what you are doing with RDBMS software and need an open source solution, you'll probably want to go with PostgreSQL -- otherwise, stick with MySQL.
Benchmark is not the most important in database choice.
I think SQLite and MySQL are quicker than Progres or Firebird but if you need some specific features like CTEs, only few database have even if it is SQL Standard
Benchmarking is hard. And expensive. And in the installations most of them are done, SQLite won't even be tested, because it's designed for completely different workloads and simply doesn't deal with the situation. (For example, any real benchmark will have clients running on different machines from the server, which SQLite AFAIK doesn't really do - whereas it does do very well in the case where you have a single client locally).
You can always look at something like spec, for example http://www.spec.org/jAppServer2004/results/jAppServer2004.html that shows both pg and mysql at least. But beware that the hardware platforms are different (and that these tests are also not from today).
But the bottom line is that if you want to compare performance for your application, the only really relevant benchmark you can run is your own application in a testing environment.
My Django project is going to be backed by a large database with several hundred thousand entries, and will need to support searching (I'll probably end up using djangosearch or a similar project.)
Which database backend is best suited to my project and why? Can you recommend any good resources for further reading?
For whatever it's worth the the creators of Django recommend PostgreSQL.
If you're not tied to any legacy
system and have the freedom to choose
a database back-end, we recommend
PostgreSQL, which achives a fine
balance between cost, features, speed
and stability. (The Definitive Guide to Django, p. 15)
As someone who recently switched a project from MySQL to Postgresql I don't regret the switch.
The main difference, from a Django point of view, is more rigorous constraint checking in Postgresql, which is a good thing, and also it's a bit more tedious to do manual schema changes (aka migrations).
There are probably 6 or so Django database migration applications out there and at least one doesn't support Postgresql. I don't consider this a disadvantage though because you can use one of the others or do them manually (which is what I prefer atm).
Full text search might be better supported for MySQL. MySQL has built-in full text search supported from within Django but it's pretty useless (no word stemming, phrase searching, etc.). I've used django-sphinx as a better option for full text searching in MySQL.
Full text searching is built-in with Postgresql 8.3 (earlier versions need TSearch module). Here's a good instructional blog post: Full-text searching in Django with PostgreSQL and tsearch2
large database with several hundred
thousand entries,
This is not large database, it's very small one.
I'd choose PostgreSQL, because it has a lot more features. Most significant it this case: in PostgreSQL you can use Python as procedural language.
Go with whichever you're more familiar with. MySQL vs PostgreSQL is an endless war. Both of them are excellent database engines and both are being used by major sites. It really doesn't matter in practice.
All the answers bring interesting information to the table, but some are a little outdated, so here's my grain of salt.
As of 1.7, migrations are now an integral feature of Django. So they documented the main differences that Django developers might want to know beforehand.
Backend Support
Migrations are supported on all backends that Django ships with, as
well as any third-party backends if they have programmed in support
for schema alteration (done via the SchemaEditor class).
However, some databases are more capable than others when it comes to schema migrations; some of the caveats are covered below.
PostgreSQL
PostgreSQL is the most capable of all the databases here in terms of schema support.
MySQL
MySQL lacks support for transactions around schema alteration operations, meaning that if a migration fails to apply you will have to manually unpick the changes in order to try again (it’s impossible to roll back to an earlier point).
In addition, MySQL will fully rewrite tables for almost every schema operation and generally takes a time proportional to the number of rows in the table to add or remove columns. On slower hardware this can be worse than a minute per million rows - adding a few columns to a table with just a few million rows could lock your site up for over ten minutes.
Finally, MySQL has relatively small limits on name lengths for columns, tables and indexes, as well as a limit on the combined size of all columns an index covers. This means that indexes that are possible on other backends will fail to be created under MySQL.
SQLite
SQLite has very little built-in schema alteration support, and so
Django attempts to emulate it by:
Creating a new table with the new schema
Copying the data across
Dropping the old table
Renaming the new table to match the original name
This process generally works well, but it can be slow and occasionally
buggy. It is not recommended that you run and migrate SQLite in a
production environment unless you are very aware of the risks and its
limitations; the support Django ships with is designed to allow
developers to use SQLite on their local machines to develop less
complex Django projects without the need for a full database.
Even if Postgresql looks better, I find it has some performances issues with Django:
Postgresql is made to handle "long connections" (connection pooling, persistant connections, etc.)
MySQL is made to handle "short connections" (connect, do your queries, disconnect, has some performances issues with a lot of open connections)
The problem is that Django does not support connection pooling or persistant connection, it has to connect/disconnect to the database at each view call.
It will works with Postgresql, but connecting to a Postgresql cost a LOT more than connecting to a MySQL database (On Postgresql, each connection has it own process, it's a lot slower than just popping a new thread in MySQL).
Then you get some features like the Query Cache that can be really useful on some cases. (But you lost the superb text search of PostgreSQL)
When a migration fails in django-south, the developers encourage you not to use MySQL:
! The South developers regret this has happened, and would
! like to gently persuade you to consider a slightly
! easier-to-deal-with DBMS (one that supports DDL transactions)
Having gone down the road of MySQL because I was familiar with it (and struggling to find a proper installer and a quick test of the slow web "workbench" interface of postgreSQL put me off), at the end of the project, after a few months after deployment, while looking into back up options, I see you have to pay for MySQL's enterprise back up features. Gotcha right at the very end.
With MySql I had to write some ugly monster raw SQL queries in Django because no select distinct per group for retrieving the latest per group query. Also looking at postgreSQL's full-text search and wishing I had used postgresSQL.
I recommend PostgreSQL even if you are familiar with MySQL, but your mileage may vary.
UPDATE: DBeaver is a great equivalent of MySql Workbench gui tool but works with PostgreSQL very nicely (and many others as its a universal DB tool).
To add to previous answers :
"Full text search might be better supported for MySQL"
The FULLTEXT index in MySQL is a joke.
It only works with MyISAM tables, so you lose ACID, Transactions, Constraints, Relations, Durability, Concurrency, etc.
INSERT/UPDATE/DELETE to a largish TEXT column (like a forum post) will a rebuild a large part of the index. If it does not fit in myisam_key_buffer, then large IO will occur. I've seen a single forum post insertion trigger 100MB or more of IO ... meanwhile the posts table is exclusiely locked !
I did some benchmarking (3 years ago, may be stale...) which showed that on large datasets, basically postgres fulltext is 10-100x faster than mysql, and Xapian 10-100x faster than postgres (but not integrated).
Other reasons not mentioned are the extremely smart query optimizer, large choice of join types (merge, hash, etc), hash aggregation, gist indexes on arrays, spatial search, etc which can result in extremely fast plans on very complicated queries.
Will this application be hosted on your own servers or by a hosting company? Make sure that if you are using a hosting company, they support the database of choice.
There is a major licensing difference between the two db that will affect you if you ever intend to distribute code using the db. MySQL's client libraries are GPL and PostegreSQL's is under a BSD like license which might be easier to work with.