I’m having an interesting conversation with my friend who’s a developer. I’m a database admin. I say file is a basic form of database. I believe whatever that stores data can be called a database. He says only engine like sql server is a database. I think he’s confused between a database and database management system? Please share your thoughts. Am I right or wrong ? Btw he agrees an excel is a database since it has rows and columns. I say a simple word document is also a simple form of database without coming into the argument of whether it’s efficient or what are it’s capabilities!
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There was lot of discussion in this question:   So much discussion that it made me confused. So... what is a database, anyway? Are only relational databases "databases"? Are object-oriented databases "databases"? Is any system that allows me to store and retrieve information (like a map, list, etc) a database?   Or does a database have to store/retrieve information and also have some administration features like Users and Privileges? Was dBase III plus a database, since it wasn't really relational?
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I've been given a Sybase .db file by a client and I need to import that into a new SQL Server database so that I may see the data as well as the tables and their relationships, any ideas on how that might be done shall be really appreciated :)
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Take the representation of an Address, here below is a complete and very detailed implementation:    here instead is a quick implementation (which more or less contains the same fields, imagine all fields in the former are contained also in the second)    If I were to decide which is the closer to a normalized and academically correct one I'd say the first one, however if I were to start a project I would go with the second.  Do you agree with this consideration? And if yes, how does one deal with this fact?   start with an easy database and as soon as it is time improve it into a more normalized/academical database. start with something as close as possible to the academical database stick with the quick and dirty solution
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Hi guys I have question about how two different Hard disk setups can possibly affect performance of my database.   I have two Options.  Option 1:  One Physical Harddisk and then Multiple Virtual hard drives for SQL Server's Database files (.mdf , .ndf),Log files, TempDB, Backups etc   Option 2:  One Physical Harddisk and then One huge Virtual hard drive for SQL Server's Database files (.mdf , .ndf),Log files, TempDB, Backups etc     To my knowledge, If these were all physical hard drives, having multiple drives for all these files (tempDB, Log file, backups, database files), would definitely benefit from  parallel processing.  But is there any drawbacks of having one massive Virtual Hard drive vs multiple Virtual Hard drives as in reality, when Sql Server is reading or writing , it will be all done from one Physical Hard disk?   Is one method preferred over other? Any suggestions or pointers in the right direction is much appreciated. Thanks
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What is the best place for storing binary files that are related to data in your database? Should you:   Store in the database with a blob Store on the filesystem with a link in the database Store in the filesystem but rename to a hash of the contents and store the hash on the database Something I've not thought of   The advantages of (1) are (among others) that atomicity of transactions is preserved. The cost is that you might dramatically increase storage (and associated streaming/backup) requirements  The goal of (3) is to preserve atomicity to some degree - if you can enforce that the filesystem you are writing to does not allow files to be changed or deleted, and always has the correct hash as filename. The idea would be to write the file to the filesystem before permitting the insert/update referencing the hash - if this transaction fails after the filesystem write but before the database DML, that is fine because the filesystem is 'faking' being the repository of all possible files and hashes - it doesn't matter if there are some files in there that are not being pointed to (and you could clean them up periodically if you are careful)  EDIT:  It looks like some RDBMSs have this covered in their individual ways - I'd be interested to know how others do it - and particularly in a solution for postgres
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I'm not an expert on database performance. A colleague has suggested splitting a BI data warehouse database into several databases based on functional business unit - I believe still on one machine though I'm not sure - for performance reasons - there are many processes, procedures, logging, and monitoring happening. This has nothing to do with security or permissions - in fact those will be made more complicated potentially.  Again I can't say I'm the expert but for some reason, it doesn't seem logical to me. DB in total is about 500 GB and we have about 200 tables. Naturally it seems like most solutions from my cursory research recommend improving the disc drive speed (like SSD) or RAM (currently an anemic 4 GB) for performance reasons. Or possibly keeping one logical database, but fragmenting the schemas into 2-3 different machines.  But I don't know. Is there a significant use case or performance reason to split one database into 2 logical databases - other than user permissions/ security which aren't a factor here. There will be many views that span across these 3-4 databases.  Do read operations, normalization, tuning options, or database/table locks come into play here? My instincts tell me no - those are entirely separate issues, but I can certainly be wrong. I'm just concerned that we are going to trade minimal, if not zero, performance improvements for a whole lot of added complexity and maintenance.  I obviously am coming in here already leaning/ biased at one side, but wondering your thoughts.
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For some of the apps I've developed (then proceeded to forget about), I've been writing plain SQL, primarily for MySQL.  Though I have used ORMs in python like , I didn't stick with them for long.  Usually it was either the documentation or complexity (from my point of view) holding me back.  I see it like this: use an ORM for portability, plain SQL if it's just going to be using one type of database. I'm really looking for advice on when to use an ORM or SQL when developing an app that needs database support.  Thinking about it, it would be far better to just use a lightweight wrapper to handle database inconsistencies vs. using an ORM.
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I want to know if I using different databases can help performance.  I have one big table support_chat with more than 5 million rows. I need to scan this all the time (3s with ajax) to check new messages on support.  If I move this table to another database in the same computer, can it help anything? (let users, sells, comments table faster)  For example:  db1  users table sells table comments table support_chat table // move this table to db2   db2  support_chat table   They want to keep old things due legal reasons, to have a user support history.
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How do I dump the data, and only the data, not the schema, of some SQLite3 tables of a database (not all the tables)? The dump should be in SQL format, as it should be easily re-entered into the database later and should be done from the command line. Something like  sqlite3 db .dump   but without dumping the schema and selecting which tables to dump.
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I just need advice on how I am going to optimize my database.  Date ---- Time ---- Area ---- Block ---- Data1 ---- Data2 ---- Data3 ---- DataN   I have that format of tables on my database. Each tables has 30-days of records with hundred thousands of records each data. Uploading of data to database is every morning. The data of yesterday will be uploaded.  The most common queries to run is grouped by Date or Date and Area or Date and Area and Block. Now, in order to make queries faster, I found out using indexes. I used indexes before. But that was when I am using a primary key. In this table, I didn't use primary key because it is totally unnecessary.   Now, I am really confused on how I am going to optimize this. Based on  on Column Considerations part, clustered index is not a good choice on Columns that undergo frequent changes. I am really confused.  Please help me if I need to use clustered index here or just non clustered or both.
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I am trying to find some database tutorials,books and similar, since I have started this course in college, and received some material, but it is really hard to manage through all the info on the net. I searched through the questions on the site but didn't find any. Thankfull for all your input.
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I'm writing an application that allows users to upload images onto the server. I expect about 20 images per day all jpeg and probably not edited/resized. (This is another question, how to resize the images on the server side before storing. Maybe someone can please drop a .NET resource for that in the comment or so).  I wonder now what the best place for storing uploaded images is.   Store the images as a file in the file system and create a record in a table with the exact path to that image. Or, store the image itself in a table using an "image" or "binary data" data type of the database server.   I see advantages and disadvantages in both.  I like a) because I can easily relocate the files and just have to change the table entry. On the other hand I don't like storing business data on the web server and I don't really want to connect the web server to any other datasource that holds business data (for security reasons)  I like b) because all the information is in one place and easily accessible by a query. On the other hand the database will get very big very soon. Outsourcing that data could be more difficult.
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Possible Duplicate:          I was wondering if there's any good reason to still use blob fields in a database. A couple of years ago I worked with a DB with a bunch of images in it, the DB was very slow and I couldn't see any good reason to keep the images inside the DB, so I got the images out and stored the filenames instead.  Was this a smart move? What would you do in my place?
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I intend to develop a small (Java) application for managing my finances. I believe I need to use an embedded database, but I have no experience regarding this issue. I tried to look at , but I can't decide which one would be more suitable for me. , ,  and  seem to be good candidates, but I still don't see how they compare to each other. I appreciate your help comparing them and helping me decide which one to use.  I intend to use Hibernate for my application (unless you would recommend using DBMS-provided API), but I also want to have the ability to edit the database easily using a SQL browsing tool (modifying schema and changing data).  Thank you.
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I am making a DB for storing reports that have following fields:  Ad_system, Ad_Campaing, Ad_Group, Keyword, Date, Impressions, Clicks, Conversions   Logic is that, Ad_system can have multiple Ad_Campaings, Ad_Campaing can have multiple Ad_Groups and Ad_Groups can have multiple Keywords, and for every Keyword there is a report. Should It be like this? Because it kind of makes sense to me, but it doesn't look correct. Primary key can also be:  ad.system.name for first table  ad.system.name ad.campaing.name for second table  ad.system.name ad.campaing.name ad.group.name for third table  ad.system.name ad.campaing.name ad.group.name keyword for fourth table  They will always be unique, but then Report will always have all DB columns in it, so it's kind of redundant.  Is the approach that I have in the diagram below correct? Or is a better one what I just described? If I am not mistaken both should satisfy 3rd NF.
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The MySQL manual at  covers this.  Usually I just dump the database and reimport it with a new name. This is not an option for very big databases. Apparently RENAME {DATABASE | SCHEMA} db_name TO new_db_name; .  This needs to work with , which stores things very differently than .
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Can someone point me to a good tutorial explaining the Entity Framework using an XML file instead of a database? I have seen some good tutorials with SQL databases, but I can't make the leap to an XML file.  Thanks!