Migrate From Oracle To Sql Server – Oracle Database and Microsoft SQL Server are two leading databases that attract the attention of global users and are ranked in the top 4 in the list of most popular databases in the world.
Oracle Database is highly compatible with various platforms and applications, and is supported by major software and hardware vendors, the community, and Oracle. The database also offers strong security and privacy functions such as authentication and data encryption.
Migrate From Oracle To Sql Server
But every rose has its thorns. Oracle database users face problems such as extensive knowledge of SQL, expensive licenses or high hardware requirements.
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Unlike Oracle Database, MS SQL Server is easier to install and configure and is automatically updated. Table partitioning, database encryption, or dynamic masking added for Oracle users are out-of-the-box in the Enterprise edition of SQL Server.
Therefore, some users are switching from Oracle to SQL Server. In general, there are two official Oracle to SQL Server converters: SQL Server Migration Assistant (SSMA) and SQL Server Integration Services (SSIS).
Some users of Oracle, SQL Server or both databases may be looking for a compatible data solution to manage them efficiently as the importance of backups cannot be overemphasized.
Backup & Recovery performs intensive backup, recovery and backup management of multiple databases including Oracle, SQL Server, MySQL, PostgreSQL with a web-based console.
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Choose from different strategies: full, incremental, differential and detailed archive backup types to choose from (varies by database). Reduces database size to save storage space, while enabling retention policies to keep data up-to-date/recovery point for automated data management.
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Oracle and SQL Server databases have their own advantages and disadvantages, users can choose one or switch to the other depending on their business needs and IT infrastructure. Microsoft is launching two Oracle to SQL Server migration tools: SQL Server Migration Assistant (SSMA) and SQL Server Integration Services (SSIS).
I have shown each step how to convert Oracle to SQL Server (see How to Migrate SQL Server to Oracle) and I hope this blog will help you. Let’s also back up these databases and manage them together, for example management with backup and restore. This round of pitfalls to avoid includes covering sequences, identity columns and filtered profiles.
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The authors are qualified experts in their field and write about subjects in which they have demonstrated expertise. All our content is tested and verified by experts in the same field.
Leonid has over 20 years as a cross-platform developer and DBA with special expertise in Oracle and SQL Server cross-platform migrations.
The first part of this series discusses the differences between Oracle Database and Microsoft SQL Server in transaction execution, focusing on issues that may be encountered during migration from Oracle to SQL Server and vice versa. This next section covers several common SQL syntax elements that are incompatible or have a completely different meaning or usage in the Oracle–SQL Server distribution.
There is a long-standing division in the data community between two camps: natural key patriots and synthetic key advocates (or “surrogates”).
Oracle Vs Sql Server Vs Postgresql
I support natural keys myself, but I often find myself creating alternatives for some reason. But with that discussion aside, let’s look at the standard mechanisms for creating synthetic keys: Oracle sequences and SQL Server identity columns.
An Oracle sequence is a first-class object at the database level. In contrast, a SQL Server identity column is a column type, not an object.
When an Oracle sequence is used to create a table key (usually a primary key), it is guaranteed to be incremented and therefore unique. But this
Consistency guaranteed. Indeed, even in well-designed applications, gaps are likely to exist. Therefore no Oracle application should rely on sequential values generated by the sequencer.
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Also, a sequence is managed using an Oracle data dictionary, so creating a dedicated sequence to support each surrogate key is time-consuming (and cumbersome). A single sequence object can support multiple or even all surrogate keys.
(the next incremental value) of a sequence, the sequence becomes a single-access critical resource. This effectively makes all processes accessing it fully sequential, turning any multi-threaded implementation (single server or multi-server) into a single process, with long latency and high memory/low CPU usage.
Such applications actually happen. The solution to this problem is to define the desired sequence object with a reasonable cache value – that is, a defined range of values (either 100 or 100k) is selected in the cache for the read process and in the dictionary. Data is recorded as it is used. And for this particular process it becomes available without having to access the dictionary every time
But this is exactly why the gap occurs because not all cache entries may be used. It also means that in multiple processes in parallel sessions, some of the recorded sequence values can be reversed in time. This reversal cannot occur in a single process unless a sequence value is reset or moved back. But this last scenario runs into a problem: it should be redundant, and if implemented incorrectly, could lead to duplicate values.
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Therefore, the only correct way to use oracle sequences is to create surrogate keys: keys that are unique but not assumed to contain other usable information that is trusted.
What about SQL Server? While sequences with very similar functionality and implementation to their Oracle counterpart were introduced in SQL Server 2012, they are not a class-leading technique. Like other additional features, it makes sense to convert from Oracle, but when implementing surrogate keys from scratch in SQL Server,
An object is a “child” of a table. It does not access any resources outside the table and its consistency is guaranteed unless it is deliberately tampered with. And it was designed specifically for that, not for semantic compatibility with Oracle.
A feature in version 12.1, it’s natural to wonder how it ever got along without it, why it implemented it now, and why SQL Server needed it in the first place (from the Sybase SQL Server sources).
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This is because Oracle has always had a key identity feature: the ROWID pseudo-column, which has a data type of
It cannot be easily manipulated (you can query, but not insert or modify), and it is generated in the background for every row in every Oracle table. Also, the most efficient way to access any row of data in an Oracle database is to use
, so it is used as a performance optimization technique. Finally, it sets the default sort order of the query output, as it effectively adds the low-level storage of row data.
In SQL Server, the first index – the primary key, is often – a cluster. This means that usually the data in the master data file is sorted by this key. On Oracle’s side, the equivalent of a clustered index is an indexed table. This is an optional structure in Oracle that is used sporadically, only when needed, for example for read-only lookup tables.
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The same is true when doing a simple transformation of SQL syntax to pass Oracle sequences to SQL Server: the code works, but using
Years ago, Microsoft SQL Server 2008 introduced several important features that made it a truly top-notch enterprise database. One that has saved my day more than once is filtered lists.
A filtered index is a nonclustered index (that is, an index that exists as its own data file) that has
Sentence. This means that the index file only contains data records related to the section. To take full advantage of filtered profiles, you must have a
Sql Server To Oracle/oracle To Sql Server Migrations, Part 2
An expression that specifies all required columns when returning a data set. When your query is optimized to use a specific filtered index that contains all the required data points, the database engine only needs to access the (small) index file without looking at the original table data file.
This was especially important to me a few years ago when I was working with a terabyte-sized table. The target customer often needed access to a fraction of the percentage of active records at any given time. The original implementation of this approach (provided by front end user interface actions) was not only painfully slow, it was simply unusable. Once I added a filtered list with the required items
S, has become a sub-millisecond search. The time I spent on this optimization task was only one hour.
Of course, filtered profiles have limitations. They cannot include LOB columns, there are restrictions on conditions
Migrate Oracle To Postgresql
Sections that indexes themselves can include and add to database storage. But if a use case meets these parameters, the storage trade-offs are usually very minor compared to the significant performance gains that filtered indexes can provide.
I later found myself on a large team at a Fortune 500 company as a developer/DBA on a SQL Server to Oracle migration project. The code surrounding the source database – SQL Server 2008 – performed poorly, with negligible performance that necessitated the conversion: the daily backup synchronization job ran for more than 23 hours.
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