Tools For Database Maintenance

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What is Data?

In simple words, data can be facts related to any object in consideration. For example, your name, age, height, weight, etc. are some data related to you. A picture, image, file, pdf, etc. can also be considered data.


A database is an organized collection of data, generally stored and accessed electronically from a computer system. Where databases are more complex they are often developed using formal design and modeling techniques. 

What is Database?

A database is a systematic collection of data. They support electronic storage and manipulation of data. Databases make data management easy.

Let us discuss a database example: An online telephone directory uses a database to store data of people, phone numbers, and other contact details. Your electricity service provider uses a database to manage billing, client-related issues, handle fault data, etc.

Let us also consider Facebook. It needs to store, manipulate, and present data related to members, their friends, member activities, messages, advertisements, and a lot more. We can provide a countless number of examples for the usage of databases.

Types of Databases

Here are some popular types of databases.

Distributed databases:

A distributed database is a type of database that has contributions from the common database and information captured by local computers. In this type of database system, the data is not in one place and is distributed at various organizations.

Relational databases:

This type of database defines database relationships in the form of tables. It is also called Relational DBMS, which is the most popular DBMS type in the market. Database example of the RDBMS system include MySQL, Oracle, and Microsoft SQL Server database.

Object-oriented databases:

This type of computers database supports the storage of all data types. The data is stored in the form of objects. The objects to be held in the database have attributes and methods that define what to do with the data. PostgreSQL is an example of an object-oriented relational DBMS.

Centralized database:

It is a centralized location, and users from different backgrounds can access this data. This type of computers databases store application procedures that help users access the data even from a remote location.

Open-source databases:

This kind of database stored information related to operations. It is mainly used in the field of marketing, employee relations, customer service, of databases.

Cloud databases:

A cloud database is a database which is optimized or built for such a virtualized environment. There are so many advantages of a cloud database, some of which can pay for storage capacity and bandwidth. It also offers scalability on-demand, along with high availability.

Data warehouses:

Data Warehouse is to facilitate a single version of truth for a company for decision making and forecasting. A Data warehouse is an information system that contains historical and commutative data from single or multiple sources. Data Warehouse concept simplifies the reporting and analysis process of the organization.

NoSQL databases:

NoSQL database is used for large sets of distributed data. There are a few big data performance problems that are effectively handled by relational databases. This type of computers database is very efficient in analyzing large-size unstructured data.

Graph databases:

A graph-oriented database uses graph theory to store, map, and query relationships. These kinds of computers databases are mostly used for analyzing interconnections. For example, an organization can use a graph database to mine data about customers from social media.

OLTP databases:

OLTP another database type which able to perform fast query processing and maintaining data integrity in multi-access environments.

Personal database:

A personal database is used to store data stored on personal computers that are smaller and easily manageable. The data is mostly used by the same department of the company and is accessed by a small group of people.

Multimodal database:

The multimodal database is a type of data processing platform that supports multiple data models that define how the certain knowledge and information in a database should be organized and arranged.

Document/JSON database:

In a document-oriented database, the data is kept in document collections, usually using the XML, JSON, BSON formats. One record can store as much data as you want, in any data type (or types) you prefer.


Database Maintenance is a term we use to describe a set of tasks that are all run with the intention to improve your database. There are routines meant to help performance, free up disk space, check for data errors, check for hardware faults, update internal statistics, and many other obscure (but important) things.

WorkSpace has always had a companion program called ‘Database Maintenance’ (or ‘System Utilities’ back before 2009) that is installed with it. Unfortunately, it is a widely unknown portion of the program. I am sure people see it in the Start Menu, but most people never click on it, which is unfortunate. The ‘Database Maintenance’ program should be run at least every 14 days in order to keep your server at its peak ‘Health’.

This article is meant to give you a little bit of a crash course on what exactly our ‘Database Maintenance’ does to your database.

Our Database Maintenance program has four main ‘Categories’ of routines:

  1. Index Defragmentation
  2. Log File Maintenance
  3. File/Data Compaction
  4. Integrity Check

Each of these categories can be run independently of each other using the new ‘Database & Server Health’ feature located in the ‘Help’ menu (version 2014.250 and newer).

1. Index Defragmentation:

SQL databases contain objects called ‘indexes’ that work a lot like the Dewey Decimal system of a library. Each table inside of your Office Tools Professional database contains at least one indexed column that we use when we need to search for a specific value (such as an Employee or a Work Code). Indexes store a sorted and partitioned copy of that data in an ultra-fast section of memory, so when ask SQL server for some specific data (such as ‘All time cards for employee ‘Joe Demo’), the database first scans the indexes for ‘Joe Demo’ to get all the row numbers for Joe’s time cards, then retrieves just those records for the application. Without an index, the database would have to read each and every single record in the table (in its entirety) to find all the records. A well-designed (and well maintained) index can improve the performance of a query by 1,000 fold or more. So creating and maintaining indexes are extremely important.

One of the things that happens to indexes are that they get fragmented, just like your hard disk does. So rather than the index being in one continuous part of memory, it is divided into numerous different parts (sometimes THOUSANDS of parts) and stored wherever there is space. And just like when your computer’s hard disk is fragmented, your database becomes extremely lethargic. In order to fix this fragmentation, our maintenance plan evaluates each index for it’s size, use, and fragmentation level and will either perform a INDEX_REORGANIZE, an INDEX_REBUILD_ONLINE, or even an INDEX_REBUILD_OFFLINE depending how bad the index is.

2. Log File Maintenance

SQL Databases contain a ‘Log File’ that keeps track of every single transaction that happens in the database. Using these log files, you can actually restore a database to the state it was at any point in time before. So if something bad happens to your database (either corruption, accidentally, or maliciously), you can recover your data as it was the instant before the event happened. So the Log files are extremely important parts of the system, and they require their own special maintenance as well.

Log files automatically grow as you add more and more data to your database. Each time the file grows, it creates a ‘Virtual Log File’ (VLF) inside that it uses to store data. Using these VLFs the SQL Server is able to find a single operation in the log file much, much faster than if it had to scan the entire log file. The downside to this is that if there are too many VLFs, the time it takes to insert data into the log file can actually increase, which harms performance. Part of our maintenance routine is to scan these VLFs and see if they are hurting performance. If the maintenance routine determines that they are, then we adjust several factors of the log file, including how large each ‘increment’ is when the log file grows. We can then compact these VLFs together to regain our lost performance (and without losing any log data).

3. File/Data Compaction

As you use your SQL database, the file size both grows and shrinks. Each time the file needs more space, it grows by a certain increment. And as data is added to the database (as a chunk), it is saved into any spot that has enough memory to store that chunk. Unfortunately, the data is not always stored close to other data from the same table. The data itself becomes fragmented, just like the indexes we talked about before. In order to resolve this issue, we run what is called a ‘Data Compaction’, which reorganizes the file by grouping all associated data together. This not only groups data together, but it can also free up space inside the file as well, which can then be reclaimed by the operating system as free disk space on your hard disc.

4. Integrity Check

Over time, your database will go through numerous changes. Data will be added and removed, tables will be added, modified, and removed. The database’s overall schema will change. Indexes will be added, rebuild, deleted, and re-created. Data columns will be added, modified, and removed. The database will go through thousands upon thousands of changes just as a natural course of its lifespan. But each change, no matter how small, has the potential to introduce corruption into the database. Indexes can have corrupt pages, table can have bad records, the schema can contain inaccurate references. These different types of corruption can cause anything from simple performance issues to complete schema failure and catastrophic data loss. But this is where the Integrity Check comes into play. The Database Integrity Check examines and analyzes the database in its entirety, and can detect and repair most any corruption it comes across. The database integrity check should be run on a regular, reoccurring, weekly schedule. The Integrity Check is your best weapon to prevent catastrophic data loss. WorkSpace has a built in Integrity Check that any OTP user with Admin rights can run on demand. If any corruption was detected or repaired, WorkSpace will immediately inform the user of the details, severity, and actions taken. In nearly all cases, that is where the corruption will end, and there will be no need for further action. But if you run an integrity check and WorkSpace reports that an issue was detected but was not resolved, please contact the Office Tools Technical Support team immediately. Our data specialists have decades of experience working with SQL Server databases and have been able to recover data that others though was completely irrecoverable.

So please, work with your IT Services and make sure that your SQL Server has a database maintenance routine scheduled to run every week. Doing this simple preventative maintenance can keep your database (and therefore your company) running at smoothly.


Optimize SQL query performance with a database maintenance solution

One of the most important elements of effective SQL Server and MySQL database maintenance is SQL query tuning. This process involves taking steps to improve the speed and efficiency of SQL queries to help ensure they don’t cause bottlenecks or slowdowns.

With SolarWinds® Database Performance Analyzer (DPA), you can get help optimizing and tuning SQL queries before bigger issues arise. DPA is designed to help you investigate and identify inefficient queries that could lead to higher I/O, longer wait times, blocking, or resource contention—all of which can interfere with database performance and, in turn, the end-user experience. DPA can let you view query details, including time ran, execution stats, and relevant metrics, you can use to tune your queries and improve overall performance. DPA also makes it easier to label specific SQL statements and exclude long-running SQL statements, as needed.

Leverage response time analysis to identify anomalies and improve performance

Use the wait time analysis feature in SolarWinds Database Performance Analyzer to enhance your database optimization DPA can pull each instance once per second to determine active session performance and alert you to any delays. When a SQL statement wait time increases significantly, you can quickly drill down to find root causes and begin a targeted troubleshooting session.

With DPA, you can also improve SQL and MySQL database maintenance results by correlating query execution delay with end-user impact. Additionally, the tools database anomaly detection algorithm is built to alert you to unexpected wait time increases as compared to normal historical data. A trend chart can also help you more easily view changes over time.

Gain insight into performance changes with a clear, unified dashboard

You can use DPA’s straightforward dashboard to help maintain Windows-specific SQL Server and open-source MySQLOracleDB2, and SAP ASE. This database maintenance software is built to pair easy-to-read bar charts and color-coded graphical displays with in-depth diagnostics, custom alerts, and robust reporting. You can also use the dashboard sharing features to explore query tuning impacts with others in the organization. With the DPA database maintenance tool, your whole team can analyze performance changes across on-premises, virtualized, and cloud environments and leverage the agentless architecture for safe SQL dev,testing and production.

Get actionable advice for query tuning and index improvement

The faster you can tune a problematic query or index, the more you reduce the chances of serious fallout from the issue. SolarWinds Database Performance Analyzer is designed to offer helpful insights based on data analysis you can use to guide your tuning and remediation efforts.

With pinpointed insights, DPA can help you formulate a database maintenance plan to help prevent performance issues. This SQL database maintenance software is built to leverage historical trends and current data to generate SQL Server tuning advice. DPA also runs table tuning analysis at the end of each day and can display table info, inefficient queries, and indexes, so you can more easily catch both minor and widespread performance issues to better prioritize those in need of immediate attention. You can also view problem query details and more easily determine if you should tune the query, add an index or columns, address fragmentation, and more.

Automate elements of the database maintenance process

With SolarWinds Database Performance Analyzer, you gain 24/7 monitoring without a 24/7 workload. You can streamline basic database administration tasks and scalability with DPA REST API, saving you time and leaving you free to focus your efforts on the tasks that demand your input. With DPA, you can also set Python or PowerShell scripts to automate key database maintenance tasks.

You can also create alerts to monitor SQL statement execution time and to automatically flag significant changes. DPA is designed to help database admins stay ahead of performance issues, with automatic anomaly detection within database operations based on an artificial intelligence algorithm.

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