Data Warehousing Service vs. Traditional Databases: What’s Right for Your Enterprise?

Today’s data-driven world requires enterprises to handle a large amount of data on a regular basis. Data is considered to be a valuable asset for most organizations as it helps them to get a better understanding of where they stand. From business intelligence and customer analytics to forecasting and compliance, it is important to make the right decision on how to store data. The valid major option includes traditional databases and modern data warehousing services that aim to fulfill the requirements. However, you might not be able to decide which is right for your enterprise. Here is some of the major information. 

To make the right decision, it is important for you to understand the differences between modern data warehousing services and traditional databases, their limitations, and advantages. So let us take a look at the details to ensure that you make the right decision. 

Understanding the basics 

• Traditional databases – Traditional databases can be referred to as a structured data repository that is primarily used for day-to-day operations. Rational databases like Oracle, SQL Server, and MySQL are some of the most common examples. These are primarily designed for transactional processing, which means that they are able to handle a large number of short online transactions like updating, deleting, and inserting data. These systems are generally optimized for Fast queries, responses, and maintaining data integrity in real-time applications like banking, software, customer management systems, and e-commerce platforms. 

• Data warehousing service – Data warehousing service, on the other hand, can be referred to as a centralized repository that has been optimized for reporting and analysis. It generally stores historical data, which is collected from multiple sources and has been designed for online analytical processing. Modern data warehousing services like Google BigQuery, Amazon Redshift, Microsoft Azure Synapse, and Snowflake are cloud native solutions. These become beneficial for businesses to handle complex queries, large-scale reporting, and advanced analytics. They generally focus on aggregating datasets and providing valuable insight through visualization, dashboards, and business intelligence tools. It focuses on aggregating vast data sets and provides insight, visualization data, intelligence tools, and a dashboard. 

Major differences between traditional databases and data warehousing services 

Usage and purpose 

Traditional databases are generally built for their operational requirements. It supports real-time business processes where the data needs to be accurate and consistent. For instance, every time a customer makes a purchase, the transaction will be recorded in the traditional database. 

On the contrary, a data warehousing service is generally utilized for analytical purposes. It can consolidate data from a wide range of systems and allow businesses to generate reports, discover trends, and make strategic decisions based on the historical data. It makes them more suitable for data analysts, scientists, and other executives rather than just frontline employees. 

Data volume and structure 

Traditional databases have the ability to handle structured data in a fixed schema. These databases are not optimized to process a humongous volume of data generated from multiple sources. The challenges are often faced by such organizations when data comes in a structured or unstructured format. 

However, modern data warehousing services clearly understand that they are created in a way to process structured, semi-structured, and unstructured data. These are able to store information and scale as the data keeps growing. Thanks to the cloud native architecture. This is what makes it an ideal choice for most enterprises and big data applications, where they are looking forward to leveraging AI and machine learning. 

Query speed and performance 

Traditional databases are able to perform exceptionally well when it comes to transactional queries like updating inventory or finding the order history of a customer. However, they might struggle when asked to make a large-scale aggregation or collaboration of massive data sets. 

A data warehousing service can be especially beneficial as it is optimized for analytical queries. The distributed computing capabilities and column storage can help businesses to process millions of rows in a few seconds. It makes complex analytical queries much faster. This can improve decision-making speed and enable real-time data analytics. 

Scalability 

One of the most significant drawbacks of traditional databases is their limited capability. Scaling up would involve expensive hardware, upgrades, and on-premises infrastructure expansion. 

However, data warehousing services, especially cloud-based solutions, can provide virtually unlimited capability. Enterprises will be able to scale their storage and computing resources independently. They will also be able to pay for what they are using. The flexibility can be particularly advantageous for businesses experiencing rapid growth or seasonal spikes. 

Management and maintenance 

Traditional databases require in-house administration for managing security, backup, index, and performance. It can be resource-intensive and costly, especially for small and mid-sized enterprises. 

On the other hand, modern data warehousing services are fully managed, which means that the providers can easily handle everything from maintenance and security to availability and updates. This enables IT teams across organizations to focus more on strategic tasks instead of routine check-ups. 

Factors to consider while choosing the right solution 

With the myriads of choices available, it is important to look into the factors before you make a decision. So here are some of the most important factors to consider while choosing traditional database and data warehousing services. 

• Nature of your business – If your enterprise relies on daily transactions and needs immediate access or updates, nothing is better than choosing a traditional database. However, if the business generally focuses on understanding sales forecasting, customer behavior, and long-term analysis, a modern data warehousing service can be a beneficial decision. 
• Variety and data volume – Organizations that have to deal with humongous data on a regular basis from multiple sources like IoT devices, third-party platforms, and social media will generally benefit from the power and flexibility offered by the modern data warehousing services. These platforms have been designed in a way to handle different kinds of data without thinking about scalability. 
• Analytical requirements – If your business depends on data science, dashboards, and predictive analytics, a traditional database is definitely a great decision. Apart from this, the modern data warehousing service integrated with machine learning platforms and tools can again be beneficial as it empowers teams to get valuable insight that they require for business growth. 
• Resources and budget – There are no denying the fact that a traditional database might have a lower upfront cost, but it demands huge in-house expertise for infrastructural maintenance. On the other hand, the modern data warehousing service might seem expensive initially, but over time, it has reduced management costs, improved ability, and provided faster insight. 

Nothing is better than choosing a hybrid approach 

There are many enterprises that value both modern and traditional solutions. Enterprises that have chosen a hybrid data architecture for their operational data are able to experience the best of both worlds. Operational data can be easily managed with traditional databases, whereas a data warehousing service can provide analytical data. Such a combined approach leverages the strengths of both systems and provides real-time operations along with supporting robust analytics. Cloud providers often provide solutions that integrate seamlessly and ensure easy data flow to maintain efficiency and operations. 

Choose Hexaview Technologies for modern data warehousing services. 

Choosing between a traditional database and the data warehousing service clearly depends on the specific operational requirements, growth, objectives, and long-term data strategy of an enterprise. Traditional database continues to play a critical role as it ensures real-time transaction processing and maintains data integrity. However, enterprises that are willing to harness the complete potential of scalability, intelligence, insight, and data analytics there is no better choice than a modern data warehousing service. However, it initially requires a complete evaluation of your current data ecosystem, goals, and capability requirements. 

Hexaview Technologies specializes in helping enterprises modernize their data infrastructure with customized solutions for data warehousing, analytics, and cloud integration. With comprehensive expertise and a technology-first approach, we make sure that organizations are able to leverage the power of modern data warehousing services. Additionally, we also provide training and ongoing support to ensure businesses leverage their complete potential.