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I have to design website to start migration of sql server from one version to another and based on client database requirements we will tell him the cost of this migration and which sql server version is best to use?
There are some important factors in choosing SQL Server version and edition on following topics:
How many CPU cores it can utilize
How much RAM it can utilize
What key feature it supports. for instance some versions do not support columnstore index or partitioning. Read the feature list.
Number/Size of supported databases
AFAIK some editions have better query optimization. (I'm not sure though)
Do you need BI feature? How about Replication, High Availability features like Mirroring? Always On? Data Encryption? Data/Index Compression?
You need to know, volume of data and concurrent users to decide.
Some features are critical for large volume databases and some are not.
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I'm hoping for some opinions on the best options for how to replicate, in real time, data from a production SQL Server database onto another SQL instance. This second instance would be for vendors who need to access some of the tables from the production database, but we would prefer that they not directly access our production instance.
I have some awareness of transactional replication and log shipping as possible solutions, but I would be interested in pros/cons of these approaches, or superior alternative solutions you may have tried.
I realize there are many topics already on Stack Overflow that discuss how to do this, but many that I found were older (technology's always changing), or focused on a very specific scenario.
For read-only access you can use AlwaysOn Availability Group feature introduced with SQL Server 2012
Documentation:
https://learn.microsoft.com/en-gb/sql/database-engine/availability-groups/windows/overview-of-always-on-availability-groups-sql-server?view=sql-server-ver15
https://learn.microsoft.com/en-gb/sql/database-engine/availability-groups/windows/configure-replication-for-always-on-availability-groups-sql-server?view=sql-server-ver15
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I have few tables that I have to sync between 3 different RDBMS systems (PostgreSQL databases, a SQL Server and a Firebird Database).
Currently I simply connect to my Firebird database and pull the few relevant tables to my PostgreSQL database, but as databases change, new tables require querying and with the addition of a SQL Server database to the mix I feel this solution is ill fitting.
I've done some research on BI tools , but I still need to query data from this data source and show them inside a Windows Forms application.
PS: it's not a migration and I only need to query the data from these "satellite" databases
Using PostgreSQL as your hub, you can use Foreign Data Wrappers to reach out to the other two databases whenever a query wants their data. Then it will always be up to date, but performance might suffer compared to actually importing the data. For reaching SQL Server, you can use tds_fdw, and for firebird you can use firebird_fdw. I have never used either one of these, so this is just a starting point.
You could probably pick SQL Server as your hub and accomplish the same thing, it calls them "linked servers" rather than Foreign Data Wrappers, see for example.
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I don't have much idea about ORDBMS features. However, I read somewhere that Oracle and SQL Server are ORDBMS. Can any one guide/tell me to know the exact differences (for Oracle and SQL Server) compare to any other non-ORDBMS (RDBMS) database?
RDBMS stands for Relational Database Management System and this is the basis for SQL, and for all modern database systems like MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access.
A Relational database management system (RDBMS) is a database management system (DBMS) that is based on the relational model.
In opposite to that an ORDBMS is an RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism.
Concrete examples might show what it is all about like this example in Oracle documenation.
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I have a question: what is the best practice for migrating SQL Server stored procedures to Oracle?
Thanks.
Best is such a fun word.
But.
Oracle SQL Developer has built in translators, including one for SQL Server.
If you capture your data model using the Migration Projects feature, it will take your T-SQL procedures and convert/translate them to their PL/SQL equivalents.
Each translation will need to be verified/approved/tested, of course.
We see somewhere between 60-90% translation success rates, that is, translated procedures being 'good, out-of-the-box.' Results will vary based on the nature of your code.
I talk about migrations, with Sybase ASE as an example, in this whitepaper. The SQL Server scenario would be pretty much the same.
We also have an ad-hoc translator, but it won't take into account your data model.
I can attest from being involved in a large production legacy project, where substantial number of "automated" options had been evaluated - none of them worked, and almost nothing they did could even be used in the 'at least that' manner.
We wasted a lot of time trying to achieve automation, and then ended up converting everything by hand, which took much less when we involved a small team of coders, once they familiarized themselves with both syntax and optimisers.
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We work to study database types.We found one of types is MPP databases. What is mean MPP Databases?, and are Oracle and SQL Server one of these databases, specifically we can create data warehouse schema ,if the MPP databases are data warehouse ?
In this context, I believe that MPP standard for "massive parallel processing".
When this term was invented, it referred to any database (or software architecture) that was scalable in hardware. This includes the ability to increase the number of the disks and processors arbitrarily -- although restructuring the data might be necessary.
Originally, databases such as Oracle, Teradata, Tandem, and DB2 were examples of MPP databases. SQL Server now has a scalable architecture, so I would put it in this category as well.
I do think that newer technologies, such as Google BigQuery are more scalable than even these products (although that might be verging on opinion).