Scalability and elasticity are related, though they are different aspects of database availability. Both scalability and elasticity help to improve availability and performance when demand is changing, especially when changes are unpredictable.
Posted March 04, 2019
Every organization that manages data using a DBMS requires a database administration group to ensure the effective use and deployment of the company's databases. And since most modern organizations rely on database systems, they also need DBAs. That said, the discipline of database administration is not well-understood, nor is it universally practiced in a coherent and easily replicated manner.
Posted February 08, 2019
Everybody knows that a database management system, or DBMS, is the system software used to store, manage, and access enterprise data. But what is a data analytics platform? Well, it can be a lot of things, so make sure that you examine any "platform" your organization is considering very carefully. A data platform might comprise a DBMS, and it might not. It might be a tool to help you collect and analyze large data sets from various sources. It might be a series of analytics tools and interfaces for accessing data. Or it might be any one, or set of, offerings that manage, virtualize, index, secure, or otherwise work with your data.
Posted January 02, 2019
Managing the performance of database systems and applications is a significant job responsibility for DBAs. From a database perspective, there are three basic performance components that must be performed.
Posted December 04, 2018
Before the end of the decade, the number of connected objects is projected to expand greatly. According to several different analysts, the number of connected objects by 2020 could be as low as 26 billion or as high as 50 billion. But even the low end of that range is quite large. Indeed, connectedness is becoming commonplace and accepted across a wide spectrum of services and applications.
Posted November 01, 2018
When you mention big data and analytics, the first thing most people think of is Hadoop, Spark, and NoSQL. But are these newer technologies required for big data projects? What about the mainframe? Mainframes are not often mentioned in big data articles and advertising. But they should be.
Posted October 10, 2018
The current trend for software development teams is to adopt a continuous delivery approach based upon DevOps and agile development techniques. DevOps is relatively a new term, coined in 2009, defining software engineering practices that combine software development (Dev) and software operations (Ops). The general idea is not really all that new, but the adoption of agile techniques and modern tooling to automate software delivery is. The goal of DevOps is for developers and operations personnel to collaborate throughout the entire service lifecycle, from design through development and into production.
Posted September 04, 2018
We are living in the age of polyglot persistence, which really just means that it makes sense to store data using the technology that best matches the way the data will be used by applications. The age of trying to force everything into a relational DBMS is over, and we now have NoSQL, NewSQL, in-memory, and Hadoop-based offerings that are being used to store data. But you really should also be looking at the algorithmic approach offered by Ancelus Database.
Posted August 08, 2018
A Worldwide Data Ethics Council is something we greatly need. The council would focus on debating, crafting and proposing clearer regulations that dictate what is—and is not—ethical in terms of data collection, retention, and usage. Furthermore, it would communicate the message of being skeptical of everything and using caution before sharing anything with anyone. The council could also work on forms of data ethics education for schools and universities, as well as to educate the press and government officials. I mean, let's face it, after watching those U.S. Congressional hearings with Mark Zuckerberg I don't think any techies believe that government officials are prepared for the Information Age.
Posted July 02, 2018
With all of the data breaches and accusations of improper data usage in the news these days, the question of who owns data looms large. Understanding who owns which data is a complex question that can't be answered quickly or easily.
Posted June 01, 2018
The relational optimizer is a very complex component of the RDBMS that we too often take for granted. The optimization techniques of the major RDBMS products continue to be improved with every new release, too. Relational optimization has saved countless hours of work and, as long as we use it properly and code our applications with knowledge of what optimization can do, the RDBMS can be used for a wide variety of requirements and use cases. Don't lose sight of that as you wend your way through the hype out there regarding new types of database systems.
Posted May 08, 2018
Data lake is a newer IT term created for a new category of data store. But just what is a data lake? According to IBM, "a data lake is a storage repository that holds an enormous amount of raw or refined data in native format until it is accessed." That makes sense. I think the most important aspect of this definition is that data is stored in its "native format." The data is not manipulated or transformed in any meaningful way; it is simply stored and cataloged for future use.
Posted April 12, 2018
DBAs spend a great deal of time monitoring and managing the performance of database systems and applications. But it doesn't have to be such a large percentage of their time. Yes, changing data patterns, requirements, and time will always conspire together to create performance problems. But more can be done to avoid the up-front poor performance of most database applications.
Posted March 07, 2018
The term "big data" has been bandied about for a number of years now, to the point where it has been used so much that it is a part of IT culture. Hard to specifically define, yet everyone seems to have a good idea what is meant by it, big data is here to stay. And that is a good thing!
Posted February 01, 2018
Blockchain is a distributed, shared, permissioned ledger for recording transactions with consensus, provenance, immutability and finality. It is the technology that drives virtual currencies like Bitcoin. But its potential spans many more industries and use cases than just virtual currencies.
Posted January 02, 2018
The importance of data to today's modern world becomes more and more clear every day. Organizations are creating, storing, gathering, and managing more data than ever before. If you are reading this article, chances are, you will agree with this statement: "You are managing more data this year than you did last year … and your organization is planning to manage even more data next year."
Posted December 01, 2017
One of the prevailing conversations around database systems lately revolves around ACID support. But not everybody knows what is meant by the term ACID. Oh, perhaps they know that it involves how data integrity is maintained or that it impacts locking. And, at a high level many folks know that relational/SQL systems support ACID whereas that is not always the case for NoSQL database systems.
Posted November 01, 2017
What Type of DBA Are You?
Posted October 18, 2017
DBAs spend a lot of time on tuning application code and SQL statements to boost efficiency and optimize access. But SQL is only one aspect of database systems performance. It is also important for DBAs to devote time to tuning and optimizing the design, parameters, and physical construction of database objects, specifically tables and indexes, and the files in which their data is stored.
Posted September 07, 2017
Referential integrity (RI) is a method for ensuring the "correctness" of data within a DBMS. People tend to oversimplify RI, stating that it is merely the identification of relationships between relational tables. It is actually much more than this. RI embodies the integrity and usability of a relationship by establishing rules that govern that relationship.
Posted August 09, 2017
As every DBA should know, DBMS data is typically persisted using disk storage. So the data is stored on disk and when it is later read or modified it has to be accessed and changed on disk. To optimize these processes, most DBMSes use a cache, or buffer pool, to stage data in memory when it is accessed. By moving the data to memory subsequent accesses to the same data can be more efficient because disk I/O can be bypassed.
Posted July 05, 2017
When a failure occurs, the DBA must ascertain whether recovery is required. It is possible, though not very likely for active databases, that a failure does not impact the integrity of your data. Assuming that recovery is required, the DBA will need to determine what resources (backup copies and log files) are available and how best to perform the needed database recovery.
Posted June 01, 2017
As DBAs, we can get mired in the depths of performance tuning parameters and scripts, sometimes getting lost in all the details. It is a good idea to always have a set of goals and philosophies that you can lean on to keep you focused and working on the appropriate things. That is what I want to talk about in this month's DBA Corner column. Some high-level rules of thumb for achieving your DBMS-related performance goals and maintaining your sanity.
Posted May 05, 2017
Every good DBA understands that backing up their database data is a non-optional part of assuring data availability and integrity. As a DBA, you need to know the difference between a full image copy backup and an incremental image copy backup and implement the proper image copy backup strategy based on application needs and database activity.
Posted April 07, 2017
The heart of any relational database management system is the system catalog that documents the database objects and system settings being used. The system catalog offers a wealth of information about your DBMS. You can think of it as the knowledge base of every piece of data known to the system. For this reason, it is important that DBAs understand what is in the system catalog, as well as how to access and manipulate the information it contains.
Posted March 02, 2017
The role of the DBA is growing and becoming more complicated in the age of digital transformation. As the amount and type of information we store expands, DBAs must become versed in administering not just one type of DBMS (e.g., relational), but multiple types (document, key/value, wide column stores, and graph) and even non-DBMS data platforms (e.g., Hadoop). Furthermore, cloud computing can change the manner in which existing applications and databases operate.
Posted February 08, 2017
The industry is changing, the way that DBAs work is changing, and database systems are changing. We all need to come to grips with the fact that the way we worked in the past is no longer the way we work with today's modern database environment.
Posted January 03, 2017
The clear trend these days is to automate and enable computerized tasks to streamline and optimize administrative and maintenance tasks. Many database management tasks that today require oversight and handholding by DBAs can, over time, be turned over to intelligently automated software to manage. But automation is just the first step.
Posted December 01, 2016
Navicat: A Helpful Toolkit for DBAs
Posted November 02, 2016
Typically, most applications consist of both batch and online workloads. This is true even today, when most of our attention has turned to online and web-based interaction. Sure, online activities are the most obvious, in-your-face component of countless applications, but batch processing still drives many actions behind the scenes. This can include applying updates, processing reports, integrating input from multiple sources and locations, data extraction, database utility processing, and more.
Posted October 07, 2016
The current driving force for many IT projects is big data and analytics. So how will the job of DBA be impacted as their companies deploy big data analytics systems? The answer, is quite a bit, but don't forget everything you already know!
Posted September 02, 2016
Regulatory compliance is a critical aspect of the IT landscape these days, and the ability to audit database activities showing who did what to which data when is a specific requirement of many industry and governmental regulations. There are six primary methods that can be used to accomplish database auditing.
Posted August 04, 2016
Database administration is undergoing some significant changes these days. The DBA, traditionally, is the technician responsible for ensuring the ongoing operational functionality and efficiency of an organization's databases and the applications that access that data. But modern DBAs are relied upon to do far more than just stoke the fires to keep database systems performing
Posted July 12, 2016
Keeping your DBMS software up-to-date can be a significant job. The typical release cycle for DBMS software is every 18 to 36 months for major releases, with constant bug fixes and maintenance updates delivered in between those major releases.
Posted June 09, 2016
Being able to assess the effectiveness and performance of your database systems and applications is one of the most important things that a DBA must be able to do. This can include online transaction response time evaluation, sizing of the batch window and determining whether it is sufficient for the workload, end-to-end response time management of distributed workload, and more. But in order to accurately gauge the effectiveness of your current environment and setup, service level agreements, or SLAs, are needed.
Posted May 04, 2016
When users require access to multiple databases on multiple servers distributed across different physical locations, database security administration can become quite complicated. The commands must be repeated for each database, and there is no central repository for easily modifying and deleting user security settings on multiple databases simultaneously. At a high level, database security boils down to answering four questions.
Posted March 31, 2016
Every DBA should take advantage of the mechanisms provided by the DBMS to ensure data integrity. When DBMS-provided methods are used, fewer data integrity problems are likely to be found. Fewer data integrity problems mean higher quality databases and more proficient end users.
Posted March 03, 2016
One of the biggest challenges facing organizations today is making sure that the right information gets to the right people. It requires attention, diligence, and planning to ensure that data is used appropriately and accurately. Unfortunately, few organizations treat data as the corporate asset it truly is.
Posted February 10, 2016
If you are a working DBA, the actual work you do these days is probably significantly different than it was when you first began work as a DBA. So is the term DBA really accurate any longer? Or has the job grown into something more?
Posted January 07, 2016
As a DBA, establishing a reasonable backup schedule for your databases can be a challenging project. It requires you to balance two competing demands: the need to take image copy backups frequently enough to assure reasonable recovery time, and the need to not interrupt daily business. The DBA must be capable of balancing these two objectives based on usage criteria and the capabilities of the DBMS.
Posted December 02, 2015
There are many different ways to look at database administration. It can be done by task, by discipline, by DBMS, by server, and so on. But one useful way to look at database administration is in terms of the type of support being delivered to applications. You can paint a broad brush stroke across the duties of the DBA and divide them into two categories: those that support development work and those that support the production systems.
Posted November 09, 2015
Too little emphasis overall is placed on the integrity and recoverability of the data—and too much is placed on performance. Yes, performance is probably the most visible aspect of database systems, at least from the perspective of the end user. But the underlying assumption of the end user is always that they want to access accurate and, usually, up-to-date data. But what good does it do to quickly access the wrong data? Anybody can provide rapid access to the wrong data!
Posted October 07, 2015
Whenever I get into a discussion about database standards I invariably bring up one of my favorite quotes on the topic: "The best thing about standards is that there are so many to choose from." It shouldn't be true, but it is.
Posted September 09, 2015
As a data professional, you have heard the term "unstructured data." And you probably know what is meant by that term, as well. For those who do not, unstructured data is a general term used to define data that is not numbers, letters, and dates stored or viewed as rows and columns. But it is a horrible term. In fact, unstructured data is a lie. Let me tell you why.
Posted August 10, 2015
You'd be surprised at the variety of sages that have uttered pithy pieces of wisdom that prove useful in some way to DBAs. So with that in mind, let's review some of the could-have-been-DBAs through history by reviewing their own words!
Posted July 08, 2015
The landscape for database management systems is changing more rapidly these days than it has since the earliest days of the relational DBMS. Not only do we have an onslaught of NoSQL database systems of various different forms (column, document, key/value, and graph databases), but we also see a burgeoning market for in-memory database management, where the DBMS relies on main memory instead of disk for data storage, management, and manipulation. But there is another "category" of DBMS evolving that is known as "NewSQL."
Posted June 09, 2015
Every now and then, somebody will raise the age-old question "How can I measure the effectiveness and quality of my DBA staff?" This can be a difficult question to answer. And it almost always hides the actual question that is begging to be asked, which is "How many DBAs do we need?"
Posted May 14, 2015
When databases are built from a well-designed data model, the resulting structures provide increased value to the organization. The value derived from the data model exhibits itself in the form of minimized redundancy, maximized data integrity, increased stability, better data sharing, increased consistency, more timely access to data, and better usability.
Posted April 06, 2015
One of the trickiest aspects of relational database management can be dealing with missing information. The standard method of representing missing information is to set the "value" to null.
Posted March 12, 2015
When the data requirements of an organization change, the databases used to store the data must also change. Unfortunately, today's database systems do not make managing database change particularly easy.
Posted February 11, 2015