I'm using DataAdapters with my SQL database with the intention of all the SELECT, UPDATE, INSERT, DELETE commands to be automatically generated.
One table is huge so I'm wondering is it more efficient to "SELECT Top(1) * FROM hugetable" instead of "SELECT * FROM hugetable" in order to facilitate the generation of commands.
I hope this isn't too confusing.
Thanks,
Geoff
So I just created a very nice dataset class with 30+ tables and relationships for a very large project. Each table has 3-8 associated queries besides the usual Fill/Get and then there will be many more in the BLL that utilize this DAL. I then created a BaseDAL class and other DAL classes that inherit from the BaseDAL(has basic sql query access if needed). What I want to know is if the way I am doing this is correct and if this is a good idea for a database of this size. I've never used TableAdapters before and I don't know if I should be using them at all? I don't know how they handle connections and if one user will have more than one connection open because of using them or will they all share an open connection?
Can someone please direct me. Thank you! Also, if you notice in the top of the UserDAL code I have listed below, I declare and initialize the usersTableAdapter and usersDeptTableAdapter. Should the call to create the object be moved into each function?Public Class Users : Inherits BaseDAL
Private usersDS As OEE_USERSTableAdapter = New OEE_USERSTableAdapter()Private usersDeptDS As OEE_USER_DEPTSTableAdapter = New OEE_USER_DEPTSTableAdapter()Private retcode As Integer = 0
#Region "USER"
' Returns employee ID if user is in system, otherwise returns 0
Public Function ValidateUser(ByVal username As String) As String
'Dim usersDS As OEE_USERSTableAdapter = New OEE_USERSTableAdapter()Dim dtUser As New OEE_USERSDataTable
dtUser = usersDS.GetUser(username)
If dtUser.Rows.Count = 1 ThenReturn dtUser.Rows(0)("EMPLID").ToString
Else
Return "0"
End IfEnd Function
'Add User
Public Function InsertUser(ByVal emplid As String, ByVal username As String) As String
Dim insertedEmplid As String = ""
emplid = usersDS.AddUser(emplid, username)Return insertedEmplid
End Function
Public Function FlagAsInactive(ByVal emplid As String) As Boolean
retcode = usersDS.FlagAsInactive(emplid)Return retcode <> 0
End Function
'Sets inactive flag to null for user (Reactivates them)
Public Function ActivateUser(ByVal emplid As String) As Boolean
retcode = usersDS.ActivateUser(emplid)
Return True
End Function
'Returns list of all usersPublic Function GetUsers() As DataTable
Return usersDS.GetUsers
End Function
#End Region
We currently have a data warehouse running on SQL 7.0, SP2. One of our primary fact tables is now well over 155 million rows in it. The table is not very wide, as it only contains 17 columns, most of which are defined as integers. The entire database is only 20 GB.
The issue is that the loads from the staging table to this fact table have significantly deteriorated over the last month or so, dropping from over 400 transactions per second to around 85. We drop all the indexes on the fact table before we load the data into it.
Are there issues with a manageable table size in SQL 7.0 that we need to be concerned about? And should we consider partitioning the table into several smaller tables and join them with a "union all" view?
I really need to get this performance issue resolved, as our IT support vendor is pushing us to port the data warehouse to UDB because they tell us that SQL server is not scalable enough to handle this volume of data.
Thanks for any help you can provide.
George M. Parker
Hi,
How can i partition the large tables so that the insert and updates which iam doing on the tables take less time.
I want to know how can i partition large tables and if i do that how is that the performance is going to be increased.
Thanks.
How can I find largest 5 or 10 tables in a database?
Thanks in advance
Chan
Hi there,i am having some problem related to SQL server........ Actually i am having a table called ZipCodes that have around 80,000 rows... and the size of the table is around 100 MB...... and my table is now on web Server,. now my problem is that when i fire some query that needs to go through whole of the table then it estimated time to execute the query comes to be 13 seconds and the corsor threshold is set to 7 seconds (and i can't change that)....... so the SQL server cancels the query to be fired........Now i need some Methodology/Technique through which i can search Large Tables with minimum calculations in minimum Time............(Any Ideas)....
View 3 Replies View RelatedIs it possible to compress the large tables in the database,
like COMPRESS, ARCHIVE options we use to reduce the size of files
stored on any operating system.
I know there is a difference between the file stored on disk and the table created in the database, but currently I am facing space problems wherein, I have to manage my database within the space available, so please advice me if the option is available in SQL Server 6.5 or 7.
I will be happy if I get the solution immediatly as currently I am facing this problem and waiting for your reply.
Thank you
Amol
I am fairly new to SQL, so please forgive me if my question is a bit elementary. I need to pull two individual tables out of a massive DB into a new DB for testing.
Thanks for the help.
I'm in the midst of a long file conversion job. Today I found that one of the tables (converted from csv) to be 6.7 million records. My sql script which I use to reconfigure the weird original date format, into something the rest of the planet uses, times out due to the size.
Does anyone please know of a file utility to automagically split sql server 2005 tables for later re-combining once my scripts have successfully completed their task on the smaller tables?
I am making a warehouse managment system. The system will cotain much data, but only a small portion of the data will be accessed frequently. Most of the data will only be accessed seldomly, but the customer wants to keep all historic data (just in case they should need it sometime). I have figured I need to partion the tables somehow to keep what is fresh in one place, and historical data in another place. What is the best way to do this? I am thinking about making historical tables. For example I can have a table named PickList and another table named PickListHistorical. When a picklist is processed/complete I can move it over to the PicklistHistorical table, but when the users need to search for a specific picklist I have to look in both tables. I can ofcourse create a view for this to make it transparant. Sql server 2005 introduced some automatically partioning. Will it be better to use this than create my own historic tables? If so, can you please tell me how I do it?
Thank you!
I've successfully created SSIS packages where I compare two tables in different databases on different servers. However, this is good enough to compare hundreds of thousands of records quickly. The process becomes a huge performance problem when trying to compare table differences when I'm looking at tables that each contain tens of millions of records.
One database is on a SQL 2005 box and the other DB is SQL 7.0 so the lookup component fails for this type of SQL Server. I've been implementing merge joins and conditional components to do my standard table comparisons.
Is there another way to implement this process or maybe partition it somehow to take pieces of the table at a time and compare them? I'm open to ideas.
I have 4 tables with the respective amount of records
1) 6755
2) 2021
3) 2021
4) 355
They all have the same columns. However, they need to be seperate, or at least when I query them. I'll be accessing this database via the web. i was first afraid that a large database would cause major slow down when accessing the db. So I broke it up into 4 tables. If I combined all 4 tables into one large table and just had a column that differentiated the 4, how significant would be the change in speed when accessing the table? It's not a big deal to keep them seperate, its just that when I have to add or remove a column from one table I have to remove it from all the tables. Furthermore, I'm using a module from DEVEXPRESS, don't know if anyone has heard of it, but when you use a gridview, it loads up the entire table even though your paging (which I think is retarded), so for that reason I was afraid it would slow up my access to the db. Any thoughts?
We are inserting into a table, which includes an identity primary key column. When the table gets really large (i.e. 1.5 million records), the performance of the inserts reduce.
I noticed that when we insert into the table an exclusive lock on the table is obtained. Do inserts into tables with identities always lock the table?
Given the table size is unavoidable, does anyone have a suggestion to improve the performance?
Thanks,
Matt
I have a few hundred users, maybe a dozen or two active at any given time, accessing the same database via ASP. The database has many tables, one being a very large orders table with a few million records, in which I have created a view against. A view only because I need to allow the user to filter quite extensively against the results. The users typically only need to view records for the last 30 days and results for each user might be five thousand records or less.
My question is this. Would I be better off writing each user's resultset to a temp table for that user's session and allow the filtering and sorting by the user go against that temp table and increase my hardware requirements to accomodate that. Possibly to the point of creating a database cluster. OR would I be better off leaving it as is where each users uses the same view.
FYI...each user may need visibility to only a hand full of fields, but over all the view must maintain many fields.
Any thoughts on this would be greatly appreciated. Thanks in advance.
Dave
Hi gurus, I'm creating a web application where I will have a large number of tables (between 10k and 20k), this is done for the sake of scalability as tables will be moved to different database servers as the application grows and also for performance (smaller indexes). I'm worried though how having a large number of tables could affect the performance of SQL Server as the application will start on one single database server. I tried to find some resources on that on the internet but couldn't find any.
I would really appreciate if you can give me some advice and if you have any good links that would be great...
I have the following table structure:
tableA (~85,000 rows) primary key = [colA,colB]
tableB (~850,000 rows) primary key = [colA,colC]
tableC (~120,000,000 rows) primary key = [colA,colB,colC]
IMPORTANT: colC is DATETIME
For a SET of rows in tableA (about 50,000) I need to pull the MOST RECENT (given a date) corresponding values from tables B and C. The only way I can think of doing this is the following:
SELECT tableA.colA
,(SELECT TOP 1 colX FROM tableB WHERE colA = tableA.colA AND colC <= @INPUTDATE ORDER BY colC desc)
,(SELECT TOP 1 colY FROM tableB WHERE colA = tableA.colA AND colC <= @INPUTDATE ORDER BY colC desc)
,... --some more columns from tableB
,(SELECT TOP 1 colX FROM tableC WHERE colA = tableA.colA AND colB = tableA.colB AND colC <= @INPUTDATE ORDER BY colC desc)
,(SELECT TOP 1 colY FROM tableC WHERE colA = tableA.colA AND colB = tableA.colB AND colC <= @INPUTDATE ORDER BY colC desc)
,... --some more columns from tableC
FROM tableA
WHERE tableA.colX = 'some criteria'
Is there any other way anyone can suggest? Unfortunately, because tableC is so large, the disk IO (I think) causes this query to take over an hour. (If I had monster RAM and super fast disk this wouldn't be as big an issue, but that's not an option right now )
Thanks in advance!
Hi gurus, I'm creating a web application where I will have a large number of tables (between 10k and 20k), this is done for the sake of scalability as tables will be moved to different database servers as the application grows and also for performance (smaller indexes). I'm worried though how having a large number of tables could affect the performance of SQL Server as the application will start on one single database server. I tried to find some resources on that on the internet but couldn't find any.
I would really appreciate if you can give me some advice and if you have any good links that would be great...
Waleed Eissa
http://www.waleedeissa.com
Hi,
I have a table with over 61 million records having a clustered index on an identity column(Primary key). Simple count queries are taking minutes to execute on this table (ex: select count(1) from table1). I have checked the statistics on the primary key which displayed me the histogram having the 39th million record as the Range-hi-key. I updated the statistics on this column and tried requerying, but still it took atleast 5 minutes to give me the count of records in the table. Also, there were no users using the table when I queried. Inserts into this table were working fine. I have other tables in my database with 41 million records having no such issues. Can anyone point me to the problem areas in such scenarios?
Thanks,
Harish
What is the best procedure/sequence to reduce some tables containing large number of rows of
a SQL 2000 server?
The idea is first to check which tables grow extremely fast (all statistics, user or log tables), reduce the table
according to the number of months the user wishes to keep in the table.
As a second step backup remaining rows of table as txt files on harddisk (using DTS), UPDATE STATISTICS and re-indexing reduced table.
Run DTS Package every month once (delete oldest month and backup newest month) and do the same as above to keep size of tables adequate.
What is a fast way to reduce number of rows of a large table - the following example produces an error (timeout expired) of my
ADO connection when executing:
SET @str = 'DELETE FROM ' + @ProcessTable + ' WHERE ' + @SelectedColumn + ' < DATEADD (m,' +' -' +
@KeepMonthsInDatabase + ',
+ GETDATE())'
EXEC (@str)
Adding ConnectionTimout = 0 did not help unfortunately.
What is the best way to re-index the table just maintained?
Thanks
mipo
We are having very big tables in TBS and wanted to setup a strategy for index maintenance.
View 3 Replies View RelatedI have come across a database system which isn't designed to work optimally. It is fairly large (~400GB) and performance of loading and querying is degrading (improper data types, fragmented indexes, non unique clustering key and other problems). So, I have quite a task in front of me, but I am up for the challenge. I figure this is not a unique situation, many of us would have come across this before. I have done this before too, but only for smaller databases, some of the operations here I expect to take a couple of hours or more to complete (depending on load/infrastructure speed etc, I know).
My plan is thus:
+ Take a full backup of the database
+ Set the recovery model of the DB to simple
+ Drop non clustered indexes
+ Drop clustered indexes
+ Remove PKs (wrong data types, too large!)
+ Narrow data types (add new column, update column in batches to old value, rename new column to old column)
+ Add PKs, which will create clustered indexes automatically based on PK ID
+ Create non clustered indexes
+ Run a SHRINKDB (normal operations I would never do this, but this is a special case, ensure log file is truncated to a logical size especially after all those table modifications...)
+ Set the recovery model of the DB to Full
+ Ensure everything works OK or better
How many no of records of the tables are called large tables.
We are getting more deadlocks. We are using default isolation. Read & insert statements are blocking each other and causes dead locks.
I am thinking that might be purging will reduce deadlocks.
The table has 15million records. Is this table consider as large table or not in OLTP systems?
In general how many records we need to consider as large table.
We have a simple UPDATE query, joining two tables, that takes much longer than 10 hours to run, but if we break the table in six (10 million rows in each table), it takes only fifteen minutes to run each part.
Why? And how can we tell in advance whether a query will cross the threshold into l.o.n.g.r.u.n.n.i.n.g query? Or, how can we prevent it?
The system is Windows XP Pro with 4GB RAM (/3GB switch), and SQL Server Standard 2005. Log files, swap files, dbf files are on separate drives. The system is dedicated to SQL Server. No other queries are running at the same time. The database is in Simple logging mode. Each table is a few GB with 60 million rows.
An example problem query is: (updating fewer than 10 bytes)
UPDATE bigtable
SET bigtable.custage = scores.custage, bigtable.custscore = scores.custscore
FROM bigtable
JOIN t2 ON bigtable.custid = scores.custid
In this case, each table has 60 million rows. 'custid' is a sequential, unique integer. SCORES table is clustered on 'custid' and is 1.5GB in size. BIGTABLE has an index on 'custid', and is 6GB in size. There is a one-to-one match between the tables on 'custid', but not enforced. The SCORES table was created by exporting a few fields (but all 60 million records) from BIGTABLE, updating the values in a separate program, then importing back in SQL Server into the SCORES table.
The first time this query was run, we stopped it after it ran 16 hours. When we broke up the bigtable into 10 million record chunks (big1, big2, big3..., big6) each update only took 15 minutes, for 90 minutes total.
* How can in we tell in advance that the full chunk would take more than a few hours?
* Why is it taking SO MUCH LONGER than in smaller chunks?
* When a query is taking that long to run, is there any way to tell where in the plan it is?
* What should we do differently?
Thanks for any help; this is a real head scratcher for us.
Hello,
I hope I am posting this in the right forum.
I am using tableDiff.exe to create a diff SQL script for a very large table (~4 million rows).
After a few minutes, I recieve a "System.OutOfMemoryException".
I have 4GB of ram on the machine executing the table diff.
The server is 32-bit, so adding ram is not an option.
I am executing the following command line:
Code Snippet
TableDiff.exe" -sourceserver "SERVER" -sourcedatabase "SourceDB" -sourcetable "Table1" -destinationserver "SERVER" -destinationdatabase "DestDB" -destinationtable "Table1" -f "C:TableDiffsTable1"
I have seen reports of other users executing tableDiff against 2million row tables.
Is there anyway to buffer tableDiff, so that I do not run out of memory on the server?
Could anything else be causing this error?
Thanks,
Dave
Hi,
I currently have a large table (35 million rows, over 80GB). I have one varchar(max) column on the table that is used in the fulltext index.
To query the complete index is fast, for example:
SELECT 'ipod', COUNT(*)
FROM CONTAINSTABLE(MyDB.dbo.Contents, [Body], 'ipod') CT
This took 70 seconds (which I can live with). However, I seldom run queries like this, most are more like:
SELECT 'ipod', COUNT(*)
FROM CONTAINSTABLE(MyDB.dbo.Contents, [Body], 'ipod') CT
JOIN Pages ITP ON ITP.PageID = CT.[Key]
JOIN Feeds ITF ON ITP.IPID = ITF.IPID
JOIN Buyers ITB ON ITB.IBID = ITF.IBID
WHERE ITB.ID IN (1342,246)
These queries are much slower (this example took 17 minutes). I understand that FT searches the index and returns all rows that match the query to SQL. SQL then performs the joins and counts only the correct results. (Correct me if I'm wrong here).
One solution I've seen to this to put data or "tags" into the FT column - so my Body column would become something like:
'{ID:1342}' + [Body]
That sounds like a very good idea. I could then change the 2nd query above to be:
SELECT 'ipod', COUNT(*)
FROM CONTAINSTABLE(MyDB.dbo.Contents, [Body], '("ID:1342" OR "ID:246") AND "ipod"') CT
That all works well until I want to select 1000 different ID's because the FT query will become very long and complex. Also I'm only including one column (ID) in this example - but I have about 7 or 8 columns that I would need to include in these "tags". Quering multiple columns become very complex quickly and no doubt I will reach a query limit at somepoint.
If anyone has any other suggestions to the above I'd love to hear them. Another thought I'm having is to partition the table. I can find very little online about how FT behaves on partitioned tables - I fear it behaves exactly the same, what I'd like to think is that I could partition the table on an ID say 100 per partition or something, and then fulltext would only search the relevant partitions. If it behaves like this it may work. If no-one knows then I'll give it ago, but this will take me a while due to the table size - so I'm hoping one of you clever lot know!
Many thanks for any advice.
Simon
I have a general SQL design-type question.
I want to log errors to a table. If the error is with a URL, I want to store the URL. These URLs can be very large, hundreds of characters, but I only need to store it if it causes the error, which should be very infrequent. Which is the better design:
Create a large varchar field in the log table to hold the URL, or null if the error wasn't with the URL.
Create a foreign key field in the log table to a second URL table, which has a unique ID and a large varchar, and only create a record in this table if the error is with the URL.
One concern I have with design 2 is that there could be many other fields that are infrequent. Do I create a separate table for every one?
Richard
hi all,
i have a large table in sql server 2005 (it has about 6 columns and 10 million records).
i need to work in a linear way on all the records (i know it sounds dumb but i need to work on all records).
now, obviously when trying to work on this table sql server get stuck for timeout or something like that...
i've noticed that a simple function like "select top 100 * from ExportTable" still works.
is there any way to have sql send me the data when it access it so that i'll still be able to proccess it on the same time, i basically work using dataset so that fixing the timeout wont be helpfull since windows probably wont allow me to load this amount of data into memory.
can any1 help?
Z
Table structure: col1 IDENTITY (seed=1 increment=1) + few other columns (col2...col7) + one text column (col 8)
I have around 50,000,000 rows per day inserted in the table T1. At the end of the day 40,000,000 rows are deleted. I have to keep the records for 12 months and then archive it. Database is 24/7 web serving and there is no down time allowed. IDENTITY column will go out of range (overflow) after less than two years, unless the identity seed is reset to the start value (seed=1, increment=1).
At the end of 12th month data is archived in another table and only last month is kept in the table T1. So table T1 enters new year with data from last month of the previous year. There are few other tables that refer to this table by using there own field with values from T1.IDENTITY column (referential integrity is not enforced). Identity column in T1 is needed as a unique id for some search actions. Performance is an issue therefore bigint data type is used for this identity column rather than decimal.
Another problem I have is how to do table update on one column (1 mil rows to be updated out of 2 mil of rows) with the minimum impact on the users who are querying this table heavily. Not need to mention that it is web app 24/7 no down time.
Thank you in advance.
Goran
We are in the middle of re-designing few tables (namely transaction tables) that would store very large data and would be hosted on cloud (Azure). The old design of this product breaks transaction tables into monthly tables. i.e. say ORDERS Table would be physically broke into twelve monthly tables over a year like ORDERS0115 (mmyy), ORDERS0215 and so on.
We are in the opinion that keeping the entire transactions in one Table is better. Would like to know what's the best practices for transaction tables like the one mentioned above? Is it better to use one table with partitions. I read somewhere that partitions can slow down SELECT queries if not designed and thought properly.Since this would be hosted on cloud (Azure), do you think some additional things are to be taken care? How a site like Amazon keeps their transactions tables?
I have a query that joins two large partitioned tables and depending on the values in the where clause, I can get dramatically different performance results.
The first query completed in around 7s and has 47,000 logical reads.
select mo.monitor_id,
mo.site_id,
mo.testtime,
sum(mo.NumBytes),
sum(mo.DNSTime),
sum(mo.ConnectTime),
sum(mo.FirstByteTime),
sum(mo.ContentTime),
sum(mo.RelocTime)
from monitor_raw mr(nolock), monitor_object mo(nolock)
where mr.monitor_id in (5339, 5341, 5342, 943842, 943866)
and mr.testtime between 'Oct 31 2007 3:00:00:000PM' and 'Nov 30 2007 3:00:00:000PM'
and mo.returncode = 200
and mr.site_id in (101,102,105,109,110,112,115,117,119,122,126,151,132,139,129,135,121,138,143,142,159,148,128,171,176,177,178,111,113,116,118,120,127,133,131,130,174,179,185,205,200,202,203,204,210,211,208,209,212,213,216,199,214,224,225,229,230,232,235,241,245,247,250,254,261,267,264,265,266,268,269)
and mr.escalationlevel = 0
and mr.monitor_id = mo.monitor_id
and mr.testtime = mo.testtime
and mr.site_id = mo.site_id group by mo.monitor_id, mo.site_id, mo.testtime
The second query takes 188s to complete and has 1.8m logical reads. The only difference between the two is the value of the monitor_ids in the where clause.
select mo.monitor_id,
mo.site_id,
mo.testtime,
sum(mo.NumBytes),
sum(mo.DNSTime),
sum(mo.ConnectTime),
sum(mo.FirstByteTime),
sum(mo.ContentTime),
sum(mo.RelocTime)
from monitor_raw mr(nolock), monitor_object mo(nolock)
where mr.monitor_id in (152682, 5339, 5341, 5342, 268080)
and mr.testtime between 'Oct 31 2007 3:00:00:000PM' and 'Nov 30 2007 3:00:00:000PM'
and mo.returncode = 200
and mr.site_id in (101,102,105,109,110,112,115,117,119,122,126,151,132,139,129,135,121,138,143,142,159,148,128,171,176,177,178,111,113,116,118,120,127,133,131,130,174,179,185,205,200,202,203,204,210,211,208,209,212,213,216,199,214,224,225,229,230,232,235,241,245,247,250,254,261,267,264,265,266,268,269)
and mr.escalationlevel = 0
and mr.monitor_id = mo.monitor_id
and mr.testtime = mo.testtime
and mr.site_id = mo.site_id group by mo.monitor_id, mo.site_id, mo.testtime
The two tables have clustered indexes on monitor_id, testtime and site_id. Comparing the execution plan, I can see why there is such a difference in performance. The second query performs a clustered index seek on the monitor_object table starting at the lowest monitor_id, testtime & site_id through the highest monitor_id, testtime & site_id. The first query performs a clustered index seek where the monitor_id, testtime and site_id equals the same values from the monitor_raw table.
My question is, how can I force the second query to use the same execution plan as the first so that I can get better performance?
One possible workaround that I could use is to execute five individual queries, one for each monitor_id and then union the results together but this would require significant code changes to my stored procs.
Thanks,
Tim
I would like to know the impacts (if any) of adding nonclustered index with included columns on large tables (these tables are populated by bulk insert from text files).
View 3 Replies View RelatedIn a Library Management database we have these tables
1) Document ( DocNo , Doc_type , permalink,inDate)
2)Title(id, DocNo,Main_Title, Other_Title)
3)Author(id , Author_Name , Author_Family,Type--Like:main author , translator ,....)
4)Publisher(id,DocNo , Name,Publisedate,address)
5)Subject(id,DocNo,Subject)
6)Description(id,DocNo,ISBN,description)--one document may have some ISBN,etc
In document table I have 500,000 records.
I want to search a word in these tables ,for example i want to search 'Computer' ,this word may be in subject or title or description and etc. How can I do this with best performance?
SQL 2012
I have a source table in the staging database stg.fact and it needs to be merged into the warehouse table whs.Fact.
stg.fact is not a delta feed it is basically an intra-day refresh.
Both tables have a last updated date so its easy to see which have changed.
It will be new (insert) or changed (update) data that I am interested in, there are no deletions.
As this could be in the millions of rows that are inserts or updates then this needs to be efficient.
I expect whs.Fact to go to >150 million rows.
When I have done this before I started with T-SQL Merge statement and that was not performant once I got to this size.
My original option was to do this is SSIS with a lookup task that marks the inserts and updates and deal with them seperately. However I set up the lookup tranformation the reference data set will have a package variable in the SQL commnd. This does not seem possible with the lookup in 2012! Currently looking at Merge Join transformation and any clever basic T-SQL that could work as this will need to be fast, and thats where I think that T-SQL may be the better route.
Both tables will have >100,000,000 rows
Both tables have the last updated date
The Tables are in different databases but on the same SQL Instance
Each table holds 5 integer columns, one Varchar, one datatime
Last time I used Merge it was a wider table with lots of columns so don't know if this would be an option.