Tag Archives: database

SQL Server Concurrency Effects

Lost Update

Happens when one transaction update overwrites another, causing the update to be lost.

Dirty Reads

Reading uncommitted records.

Phantom Reads

Reading while another transaction is adding new record, result in different number of rows being returned.

Repeatable Reads

When the same query to read is executed, it will return the same result.



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Posted by on May 22, 2018 in General


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Columnstore Index

  • New in SQL Server 2012.
  • Stored by columns, a column-based index, instead of row-based like in traditional index. For example, if row-based index is consisted of Firstname and Lastname columns, the column-based index would have 2 different indexes: Firstname in its own index and Lastname in its own index.
  • The index is compressed, allowing high performance.
  • The compressed data is stored in-memory, reducing needs to read off the disks.
  • Compression ratio is generally high because the same data type in a column.
  • Generally a better choice for wide table with many columns, as commonly found in data warehouse tables.
  • Clustered and non-clustered index.
  • Can be combined with row-based index.

Microsoft Docs

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Posted by on May 16, 2018 in General


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Optimistic Concurrency x Eventual Consistency

Optimistic Concurrency

Less strict locking to support more simultaneous access. In optimistic concurrency, multi users are able to perform actions on the same resources without locking each other, for example, one user can write without locking another user that’s reading the same resource. Some actions will still lock the resource exclusively, for example, a schema changes.

Pessimistic Concurrency

Is the opposite, a stricter locking is used. When a user is performing an action that requires lock, other users won’t be able to do anything that would conflict with the lock, until the lock is release from the owner (first user).

Eventual Consistency

Eventual consistency guarantees more of availability than consistent data. This is achieved by prioritize availability (not locking the resource) rather than replicating the data.

Strong Consistency

The opposite of eventual consistency where it’s prioritizing consistent data across the system rather than availability.


Eventual consistency is classified as BASE (Basically Available, Soft state, Eventual consistency) semantics, as oppose to ACID principle.


Eventual / strong consistency is similar to optimistic / pessimistic concurrency. The difference is the terms eventual / strong consistency is often used in a distributed system where optimistic / pessimistic concurrency is used more in lower level, single entity such as database.

Azure Cosmos DB consistency levels, strong to weakest consistency:
– Strong consistency
– Bounded staleness
– Session
– Consistent prefix
– Eventual consistency

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Posted by on May 12, 2018 in General


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SQL Server Isolation Level


Isolation is the “I” in ACID principal which rules the transactional state and its concurrency. The higher the isolation level, the lower the concurrency effects. And vice versa.

ISO Standard Isolation

The ISO standard defines 4 different isolation levels, from lowest to highest:
– Read uncommitted
– Read committed
– Repeatable read
– Serializable, where transactions are completely isolated from one another.

SQL Server Database Isolation

SQL Server Database supports all levels of isolation defined by ISO standard. In addition, it adds another isolation levels: the Snapshot isolation level (ALLOW_SNAPSHOT_ISOLATION).

SQL Server Database also add another implementation of Read Committed isolation level: Read Committed Snapshot Isolation or RCSI (READ_COMMITTED_SNAPSHOT). The original Read Committed implementation is referred to RC.

In Azure SQL Database, the default setting for Read Committed is RCSI (both ALLOW_SNAPSHOT_ISOLATION and READ_COMMITTED_SNAPSHOT are set to ON).

In on-premise SQL Server, the default is RC (both ALLOW_SNAPSHOT_ISOLATION and READ_COMMITTED_SNAPSHOT are set to OFF). But can be set to use RCSI by setting them to ON.

These two isolation levels, Snapshot isolation and RCSI, use row versioning that is maintained in tempdb.


To check database settings for Snapshot isolation:

SELECT name, snapshot_isolation_state, is_read_committed_snapshot_on FROM sys.databases

To check current connection’s transaction isolation level:

SELECT CASE transaction_isolation_level
WHEN 0 THEN 'Unspecified'
WHEN 1 THEN 'ReadUncommitted'
WHEN 2 THEN 'ReadCommitted'
WHEN 3 THEN 'Repeatable'
WHEN 4 THEN 'Serializable'
FROM sys.dm_exec_sessions

To set transaction isolation level for current connection. Transaction isolation level is per session / connection.


Isolation Level and Concurrency Effects Matrix

Isolation Level Dirty Read Lost Update Non Repeatable Read Phantom
Read uncommitted Yes Yes Yes Yes
Read committed No Yes Yes Yes
Repeatable read No No No Yes
Snapshot No No No No
Serializable No No No No


In a load test, performance is significantly higher in RCSI, but it requires a lot higher throughput in tempdb (some 50x larger I/O). So planning on tempdb scaling is very important.

Microsoft Docs
Technet Blog

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Posted by on May 7, 2018 in General


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Database ACID Principal

ACID – Atomicity, Consistency, Isolation, Durability


Requires that each transaction be “all or nothing”.


Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers.


Ensures that the concurrent execution of transactions results in a system state that would be obtained if transactions were executed sequentially.
A lower isolation level increases the ability to access the same data at the same time, but increases the number of concurrency effects (such as dirty reads or lost updates) users might encounter.


Once a transaction has been committed, it will remain so, even in the event of power loss, crashes, or errors. Store in non-volatile memory.




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Posted by on May 2, 2018 in General


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Rename Table and Column Name in EF Code First

Business rules change over the time. For developers, this can be frustrating. Especially after you have spent enormous amount of time to name your objects properly. After all, we all know naming is the most prominent process of the development.. 🙂

Luckily, in Entity Framework, you can change table names quite easily.

Two ways, using data annotation and Fluent API. (Code is in Entity Framework 6)

Data Annotations

using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;

// Change table name to People
public class Employee
    // Change column name to PersonId
    public int Id { get; set; }
    public Guid DepartmentId { get; set; }
    public int CompanyId { get; set; }
    public string Firstname { get; set; }
    public string Lastname { get; set; }


Context file (inherit from DbContext)

using System.Data.Entity;

protected override void OnModelCreating(DbModelBuilder modelBuilder)
    // Change column name to PersonId
        .Property(p => p.Id)

    // Change table name to People
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Posted by on June 18, 2015 in General


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Add Authentication to MongoDB Database

To prevent un-authorized access to your MongoDB database, you can add security to it by requiring authentication whenever someone tries to connect.

It’s simple, run the mongod with --auth option. the command is:

// To add user
> use admin;
> db.addUser('admin','123456');

// Start mongod with --auth
$ sudo mongod --auth --dbpath /data

// Run mongo and login
$ mongo localhost:27017
> use admin
> db.auth('admin','123456');

// Include login in mongo command
$ mongo localhost:456789/admin -u admin-p 123456

More MongoDB security option:

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Posted by on May 7, 2015 in General


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