The Best Way to Manage Queries on Multiple Platforms

Modern database teams need to navigate increasingly complex computing environments that often include working with more than one platform simultaneously. As development strategies such as DevOps become more entrenched in the business world, the lines that separate dedicated roles are becoming blurred. Former operators are running queries and DBAs are constructing intricate scripts as they work together to streamline the process of delivering useful applications. It can be difficult to keep things moving in the right direction.

The diversity of database platforms undoubtedly contributes to the stresses inflicted on DBAs and database developers. There are many differences in implementation that may make a particular choice more or less suitable for specific uses. The team is expected to get the job done despite needing to employ an alternate mindset when approaching a problem. Let’s look at some of the major issues that need to be handled by database teams every day.

SQL Versus NoSQL

You can differentiate databases in various ways. From a high-level view, a logical point of comparison can be made between SQL and NoSQL platforms. While both types of databases may be able to solve a particular business problem, there are substantial differences that database teams need to understand and incorporate into how they write and manage their queries and develop applications. Here is a breakdown of some of the major deviations in the underlying philosophy of these two families of database platforms.


  • Scaleability with SQL databases requires users to spread data out across different servers. It can become a complex undertaking to provision tables and servers in an optimized fashion as the volume of data increases.

  • Complexity is another consideration that needs to be understood when opting for an SQL database solution. Database design needs to conform to a table paradigm and can again become unwieldy when large volumes of data are being processed.

  • Data storage is done using tables and rows employing algebraic set theory. Data must be put into a form that can fit into these tables.


  • Scaleability is handled more efficiently with NoSQL databases as it automatically spreads data onto multiple servers. This is one of the reasons for the popularity of NoSQL solutions. Its ability to scale easily assists with the seemingly unending need to expand systems to handle the growing flow of data businesses must use effectively.

  • NoSQL handles complexity by spreading data over without the need for a defined structure. It also can cache data in system memory which can radically improve retrieval time.

  • Storage is enacted with JSON-like documents and schemas, making it more flexible. Collections are used instead of tables.

Obtaining Information From Your Databases

Based on the different architectures and functionality of  SQL and NoSQL databases, pulling out the required data may require variable approaches. Database queries all follow a similar pattern where the engine parses, optimizes and then executes the instructions, hopefully returning the desired results. This is the heart of database operations, as having all the data in the world is useless if it cannot be used to answer questions pertinent to your business goals.

The general format of requesting information from a database is done using more specific techniques and tools. Specifically, DBAs and developers may use scripting languages to automate routine tasks and perform other operations on their databases. Scripting languages are usually more accessible but often have somewhat limited capabilities and do not require compilation before execution.

More intricate programming is done with interpreted languages such as JavaScript or Python. They offer extended functionality over scripting tools with the addition of more complex structures that require training to use productively. Depending on the platform, users can avail themselves of procedures or user-defined functions to unlock the utility of the data stored in their systems.

A Tool For All Your Database Platforms

Moving back and forth between systems that exhibit conceptual differences can be challenging for the most experienced team. The use of tools that can minimize complexity can lead to great productivity gains. A substantial amount of a DBA’s time can be spent moving from tool to tool to manage their multiple responsibilities. It can add another layer of confusion that they just don’t need.

Aqua Data Studio is an excellent tool to help mitigate the complexity faced by database professionals. It simplifies the life of your team by providing a versatile database IDE from which they can manage all of their diverse database platforms. It provides management and visual analytic capabilities for relational, NoSQL, and cloud databases.

Working from a single interface eliminates the inevitable small stumbles that accrue when moving between multiple tools that may perform similar functions in slightly different ways. This adds up to a lot of time over a week, month or year. Aqua Data Studio can make your team substantially more productive by just this one aspect of the tool. Using the full feature set of the application will only increase the degree of this benefit.

A webcast is available that drills down into the many ways Aqua Data Studio can help a database team handle the multi-platform world in which they operate. Check it out if you are a database professional tasked with supporting multiple platforms. Then ask yourself how much more efficiently you will get your work done by adopting the tool in your shop. The answer may result in a pleasant surprise that has you lobbying for management to get Aqua Data Studio installed in your environment as soon as possible.