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Data management is the whole process of organizing and maintaining company data. It entails collecting, validating, storing, and processing data. A database management system (DBMS) or data management system is crucial in executing the above processes, which is why businesses should take the time to understand the options at their disposal before making a choice. Here are some crucial factors that can help determine your choice of a database management system: One of the oldest ways to determine the reliability of a digital system is by looking at its age. Most DBMSs on the market today are new creations. While these systems have plenty to offer, they are usually accompanied by small shortcomings that can cause huge inconveniences in the long run. This guide to compare MySQL vs PostgreSQL performance can help you understand the basic features of established database management systems, along with what sets them apart from their up-and-coming counterparts.
Various data management systems have different data capacities, meaning not all options can store and process all the data on your hands. When choosing a DBMS, it is wise for an organization to consider its current capacity requirements, and any expansion and data increase expectations. While scalability and future data volume requirements are crucial considerations, you can’t overlook the cost of implementing a database management strategy. Your new investment should fall within your budget frames and be aligned with your organization’s core financial and non-financial objectives and existing sales and marketing strategies. Among the factors that dictate the cost of a DBMS is whether the software will be server-based, desktop-based, or cloud-based. Note that each of these options have their pros and cons that aren’t necessarily cost-related, so take the time to review them separately. Business productivity and efficiency are partially dictated by its software’s user interface. It is vital that you pay attention to a DBMS’s usability from various viewpoints, including the number of active users it can support at a time, visualization, and overall ease of use. You should also consider ease of reporting, applicable report generation formats, operating system, and framework compatibility, and report exportation formats. If a database doesn’t guarantee the safety and security of your business, employee, and customer information, it shouldn’t be anywhere near your list of options. Data security and privacy are paramount in a world where hackers exploit even the smallest of vulnerabilities. Don’t forget to take physical risks such as fires and theft into account while working to enhance security against cybercriminals and other online threats. EndnoteThe list of things to consider when choosing a database management system is endless. The above tips are some of the most important ones if you are looking for a place to start or are new to the whole concept of data management. You can also consult an IT expert for a more informed decision. Top 10 considerations when choosing a Database Management systemWhen you are confident combining your various data sources and handling all the updates, you maywell be looking to source a Database Management and Business Intelligence system.Because selection and implementation of such a system can be a complex process and involvevarious teams or personnel, we take a look here at the main factors to consider when making yourdecision, to help you with the whole process.Ensure that the system has the capacity to grow with your data and your business.1) UsabilityConsider how user-friendly the system will be for all those members of staff required to use it. Insome organisations those may include Marketing professionals, the IT department, DatabaseDevelopers and others. Look at the suitability from everyone’s perspective, and consider if you canset different levels of permission for different teams or personnel. Many systems offer drag-and-dropexecution, which makes for an intuitive working methodology. Importantly, however the systemworks, make sure it is usable for your whole team.2) Visualisation & ReportingReview the ease of visually analysing and displaying results for any queries you run on your data,while making selections and deciding segments. Also, check how the software displays campaignresults if you feed this information back into the database. You should look for visual displays thatwill help you show selections and results to colleagues (likely other teams or managers/directors) ina way that they will be able to understand quickly and easily.3) SecuritySecurity of your data is an essential aspect of any database implementation. Business-sensitive dataand any personal information you hold must be stored securely to adhere to regulations and toprotect it from loss or theft. It is important to consider both the physical risk to data (e.g., the riskfrom fire, theft, etc.) and the risks from hacking, or from unintentional corruption of data throughhuman error. Any system you implement must address the issue of keeping your data secure.4) FunctionalityConfirm that the modules available in the data analysis software meet your business requirements.
September 6, 2018 | Database
In part one of this series, we discussed the different types of databases available on the market today. In part two, we discussed how to choose the right database for your requirements. Today, we are going to look at some additional factors you should consider when selecting a database. Let’s get started. Watch the on-demand webcast: How to Conduct a Database Design Review Additional Factors to Consider When Choosing a DatabaseAfter reviewing the first two posts, we know a bit more about the types of databases, as well as how they function and what problems they can solve. And we looked at the CAP theorem as one way to help evaluate which database engine will meet your requirements. But the reality is that there are many additional factors to consider when selecting a database engine. I’ve mentioned a few already, but let’s build a list and add some commentary.ACID vs. BASERelational database engines do ACID (Atomicity, Consistency, Isolation, and Durability) very well, whereas NoSQL engines use BASE (Basic Availability, Soft-state, and Eventual consistency) to achieve the performance offered through horizontal scaling, high availability (HA), and fault tolerance. This is why I wrote in part one that relational systems tend to favor writes, and NoSQL systems tend to favor reads.AvailabilityYour database engine must have the ability to be highly available. However, that may come at a high price. For example, clustering or adding nodes will also increase hardware and software costs. Make certain you understand the topology of the HA architecture and all associated costs.Disaster RecoveryYou should review your disaster recovery plans to make certain your database engine meets your requirements and defined SLAs. If it takes too long to backup and restore, you may not want that engine. Or, if backups aren’t an option, and you need to restore or recreate a bunch of flat files, you’ll want to know that before disaster strikes. Oh, and before I forget, here is your reminder that HA != DR.PerformanceOne of the most nebulous statements out there today: “that database doesn’t perform well.” You must understand your ratios of reads to writes and if your database engine is designed to maximize one or the other (or both). Also, you should understand that fast database performance may be a result of a tradeoff somewhere else. For example, you may be promised amazeballs transaction velocity, but it’s the result of weaker consistency. If you need strong consistency, then you may not get the throughput you are promised.Complementary TechnologiesChances are you will be looking to use some other piece of technology, such as Spark, Kafka, or RedisCache. You should consider if your engine is robust enough to connect with these other platforms as needed, or if you will need to spend the time and money to build the hooks yourself.ETLSpeaking of complementary technologies, you will probably need to be moving data into and out of that database. If you already have a preferred ETL (Extract, Transform, and Load) provider, make certain it will work with your choice of database engine.Infrastructure OptionsThe database engine may require you to provide the infrastructure necessary for operations. Or it could be part of a larger data platform offering by a major cloud provider. Another item to consider here is one of data migrations. Spend the time evaluating the effort required to move your data as needed.VendorsYou may already have a preferred infrastructure vendor, such as Microsoft or AWS. If so, then your costs may be greatly reduced by leveraging an existing partnership. Otherwise, you may find the time, money, and effort required to bring on new hires with the necessary skills for your chosen database engine to be prohibitive.Monitoring and AlertingWhatever database you choose, you will want to make certain you can monitor, alert, and act upon the alerts as necessary. You don’t want to decide on a database solution that also requires you to roll your own monitoring solution. Or, maybe you do, but you should factor that as an additional expense, including the potential for needing to bring in some expertise.Business SupportAt the end of the day, if you don’t have a champion for your choice of database engine on the business side of the fence, then your project won’t go anywhere. If you’ve read this far, then take this advice: Get a champion first, before you invest too much of your time, effort, blood, sweat, and tears into selecting the perfect database(s).SummaryThe complex systems of today require multiple database engines to provide efficient solutions that a single engine of yesterday cannot. The major database vendors are adding cross-functionality support (relational and non-relational features) to their products in response to the needs of their customers. As a result, many of today’s database engines appear to be similar to one another, and it can be difficult to understand what the term “database” even means. It is my hope that you can use this article as a guide to navigate the world of relational versus NoSQL database engines.Referenceshttps://db-engines.com/en/ https://techcrunch.com/2017/05/10/with-cosmos-db-microsoft-wants-to-build-one-database-to-rule-them-all/ https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels https://www.allthingsdistributed.com/2018/06/purpose-built-databases-in-aws.html
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Top 10 considerations when choosing a database management system
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