Managing the database challenges that you face as an organization is no easy task, and you need to keep several business considerations in mind. You need to balance your vision of the perfect database solution against real-life constraints such as IT budgets, service-level agreements (SLAs), and the risks and rewards of any particular option.
Trying to enact database management strategies in place without a long-term strategy could end up creating even more problems further down the line. That could mean decreased database performance, running out of resources, application downtime and frustrated staff.
Before discussing tactics for managing database complexity, we’ll give a brief overview of two great debates in the database world: SQL vs. NoSQL, and cloud vs. on-premises. In many cases, your answers to these two questions will play a vital role in your options moving forward and the difficulty of managing your databases.
SQL vs. NoSQL Databases
SQL databases are also known as “relational databases” because they arrange data in tables with predefined schemas. The most popular SQL database solutions include Oracle, MySQL, IBM Db2, and Microsoft SQL Server.
The only unifying factor among NoSQL databases is that they don’t use the relational model. Information in NoSQL databases may be stored as documents, graphs, key-value pairs, or a number of different models. This provides greater flexibility, but at the cost of predictability and structure.
SQL databases are easier to scale vertically, which means that you can increase their capacity and performance by adding more hardware components such as processors, memory, and storage. On the other hand, NoSQL databases are easier to scale horizontally, which means that you can handle load increases by running multiple instances of the database on separate servers.
In many cases, NoSQL is better suited to handle large volumes of highly complex information. Data for some use cases, such as molecular modeling and engineering, is often so complex that it’s hard to fit into a standard tabular SQL database.
On-Premises vs. Cloud Databases
Another crucial consideration when managing database complexity is whether to run on-premises or in the cloud.
On-premises databases operate on hardware that your organization owns and maintains itself. Cloud databases, on the other hand, are stored and run on remote servers and provisioned to your organization remotely via an Internet connection. There are also “hybrid” solutions that combine on-premises and cloud solutions in a way that best fits your organization’s requirements.
There’s no easy answer to the question of whether to use an on-premises or cloud database. In the vast majority of cases, however, cloud databases have reached feature parity with on-premises solutions, and many of them have surpassed their on-premises equivalents. Likewise, software tools for managing database complexity are available in both cloud and on-premises environments.
What is clear is that for most applications, the future of business data and analytics lies in the cloud. Market intelligence firm IDC predicts that by 2025, 49 percent of all data will be stored in public cloud environments.
Databases are only going to get larger and more complicated in the future, so it’s important to know how to manage this business environment, and what choices are best for your organization.
Is your enterprise database becoming too complex for you to handle alone? Reach out to a skilled, experienced technology partner like Datavail. We’ve helped countless clients navigate database innovation by adopting the best tools and strategies for their situation.
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Most people will encounter this error when their application tries to connect to an Oracle database service, but it can also be raised by one database instance trying to connect to another database service via a database link.
Imagine over 100 logins on the source server, you need to migrate them to the destination server. Wouldn’t it be awesome if we could automate the process?