Database that can handle >500 millions rows

I am looking for a database that could handle (create an index on a column in a reasonable time and provide results for select queries in less than 3 sec) more than 500 millions rows. Would Postgresql or Msql on low end machine (Core 2 CPU 6600, 4GB, 64 bit system, Windows VISTA) handle such a large number of rows?

Update: Asking this question, I am looking for information which database I should use on a low end machine in order to provide results to select questions with one or two fields specified in where clause. No joins. I need to create indices -- it can not take ages like on mysql -- to achieve sufficient performance for my select queries. This machine is a test PC to perform an experiment.

The table schema:

 create table mapper {
        key VARCHAR(1000),
        attr1 VARCHAR (100),
        attr1 INT,
        attr2 INT,
        value VARCHAR (2000),
        PRIMARY KEY (key),
        INDEX (attr1), 
        INDEX (attr2)   
    }

MSSQL can handle that many rows just fine. The query time is completely dependent on a lot more factors than just simple row count.

For example, it's going to depend on:

1. how many joins those queries do
2. how well your indexes are set up
3. how much ram is in the machine
4. speed and number of processors
5. type and spindle speed of hard drives
6. size of the row/amount of data returned in the query
7. Network interface speed / latency

It's very easy to have a small (less than 10,000 rows) table which would take a couple minutes to execute a query against. For example, using lots of joins, functions in the where clause, and zero indexes on a Atom processor with 512MB of total ram. ;)

It takes a bit more work to make sure all of your indexes and foreign key relationships are good, that your queries are optimized to eliminate needless function calls and only return the data you actually need. Also, you'll need fast hardware.

It all boils down to how much money you want to spend, the quality of the dev team, and the size of the data rows you are dealing with.

UPDATE Updating due to changes in the question.

The amount of information here is still not enough to give a real world answer. You are going to just have to test it and adjust your database design and hardware as necessary.

For example, I could very easily have 1 billion rows in a table on a machine with those specs and run a "select top(1) id from tableA (nolock)" query and get an answer in milliseconds. By the same token, you can execute a "select * from tablea" query and it take a while because although the query executed quickly, transferring all of that data across the wire takes awhile.

Point is, you have to test. Which means, setting up the server, creating some of your tables, and populating them. Then you have to go through performance tuning to get your queries and indexes right. As part of the performance tuning you're going to uncover not only how the queries need to be restructured but also exactly what parts of the machine might need to be replaced (ie: disk, more ram, cpu, etc) based on the lock and wait types.

I'd highly recommend you hire (or contract) one or two DBAs to do this for you.

Most databases can handle this, it's about what you are going to do with this data and how you do it. Lots of RAM will help.

I would start with PostgreSQL, it's for free and has no limits on RAM (unlike SQL Server Express) and no potential problems with licences (too many processors, etc.). But it's also my work :)

Pretty much every non-stupid database can handle a billion rows today easily. 500 million is doable even on 32 bit systems (albeit 64 bit really helps).

The main problem is:

• You need to have enough RAM. How much is enough depends on your queries.
• You need to have a good enough disc subsystem. This pretty much means if you want to do large selects, then a single platter for everything is totally out of the question. Many spindles (or a SSD) are needed to handle the IO load.

Both Postgres as well as Mysql can easily handle 500 million rows. On proper hardware.

What you want to look at is the table size limit the database software imposes. For example, as of this writing, MySQL InnoDB has a limit of 64 TB per table, while PostgreSQL has a limit of 32 TB per table; neither limits the number of rows per table. If correctly configured, these database systems should not have trouble handling tens or hundreds of billions of rows (if each row is small enough), let alone 500 million rows.

For best performance handling extremely large amounts of data, you should have sufficient disk space and good disk performance—which can be achieved with disks in an appropriate RAID—and large amounts of memory coupled with a fast processor(s) (ideally server-grade Intel Xeon or AMD Opteron processors). Needless to say, you'll also need to make sure your database system is configured for optimal performance and that your tables are indexed properly.