Data warehouse cost comparison
There is no business without data. Many companies could not function without having the information extracted from the collected and analysed data. Virtually every company must gather and draw smaller or critical conclusions from data for various purposes, from forecasting market trends to better production planning and user profiling to match personalised ads. Frequently, a simple database may not be a sufficient tool. Then it would be best if you implement a close cousin of this solution – the data warehouse. It sounds like a big undertaking, and it actually involves both vast amounts of data, business intelligence and advanced analytics. Data warehouse responds to many business needs but requires good planning of the entire logic of the system, its purpose and design. Cloud solution or local infrastructure? Or maybe your own dedicated software? How much will it cost me? Many points need to be addressed before making a final decision. See the details of data warehouses below for some essential knowledge.
What is a data warehouse?
A data warehouse is a type of database used for reporting and analysis that is organised and optimised for a given topic. It is considered the fundamental element of business intelligence. Data warehouses DW are central repositories of integrated data from one or more different sources that keep current and historical data in one place. So in practice, data warehouses are databases that incorporate data from all other database systems in the enterprise. The warehouse consists of thematically oriented data sets. This data can be used to create analytical reports and be available to all company employees with a given data warehouse. It is a higher level of abstraction than a traditional relational database, but it is created with similar technologies. The data warehouse architecture is oriented towards optimisation of the search speed and the most effective content analysis.
Cloud data warehouses are a popular approach today. Unlike the on-premises system, a cloud data warehouse does not require installation on the company’s infrastructure that requires physical servers and hardware. Cloud storage seems cheaper then but also has its downsides, so it is not an obvious choice.
When to use data warehouse?
A data warehouse can be used in enterprises for various purposes. First of all, data warehouses are used to store data in one optimised environment that will be the central repository and the ultimate source of truth in case of doubt. Data warehouses can also be a tool for advanced data analysis, and such analysed data can then be used to generate reports or forecast future events. So if your business has a lot of processes relying on data and the research done on it, a data warehouse can be a perfect choice.
Moreover, data warehouses can be part of an integrated system, e.g. in combination with Google Analytics. The data warehouse brings together all data in one place, unifies it and thus facilitates further operations. It helps to better and easier compare data, analyse and use for advanced visualisations or reports. Most data warehouses on the market can automatically download data from one or more sources, such as the Internet, and simplify data integration. The data warehouse can then convert this information to the selected format, categorise it appropriately and make it easier to manage.
To briefly sum up, data warehouses facilitate data storage and compute, analyse and manage it efficiently.
What affects the price of a data warehouse?
Unsurprisingly, several major factors affect the cost of a data warehouse. It is definitely worth thinking about them when choosing a solution for your business.
Data storage system
First of all, the way the data is stored. Data warehouses can be installed locally, on-premises, which will require the infrastructure the company needs to assemble and buy. Consequently, such a data warehouse will require a high initial investment, as well as constant maintenance and, if necessary, scaling and enlarging the storage space, subsequent expenses. However, it is a solution that ensures effective and quick data transfer between locations and gives you complete control over the system. An alternative solution that is currently very popular and is constantly expanding is a cloud data warehouse. These kinds of data warehouses do not require extensive local hardware or space as it is provided over the Internet. They allow access from anywhere in the world, and therefore remote work. They also keep the staff required to operate the on-site data warehouse and the equipment to a minimum. Less equipment also translates into lower operating costs such as electricity, office space rental, etc. Cloud data warehouses can be a bit slower than on-premises, however, as the servers may be in different locations. However, it is a cheaper option.
Another thing is the ETL system. ETL means Extract, Transform and Load and refers to operations performed on data stored in a data warehouse. Basically, the ETL solution deals with moving data from different data sources, and you have various available tools on the market. In the case of ETL tools, each tool typically supports a different set of databases. For this reason, it is crucial to make sure that the chosen solution is correctly synchronised with the data you want to store in the data warehouse. In terms of costs, there are also various pricing models for ready-made solutions. The fixed-rate pricing model starts at a single price and stays the same; you can pay a fixed rate per month or per year. The staircase model increases by fixed amounts based on predictable factors such as the increasing amount of data stored. You can also choose to write code and scripts for ETL in-house. It allows the tool to be tailored to the business needs, but it will be more time-consuming. Hence, it all depends on the individual requirements of the enterprise.
The next factor that can affect the data warehouse price in the case of software is the data visualisation and business intelligence tools. Thanks to these solutions, you can use data warehouses much more efficiently and extract valuable information from the collected data. Visualisation is an interdisciplinary field dealing with the graphical representation of data, and such presentation of information is much better at reaching the recipients. Business intelligence tools are software that helps you process and analyse large amounts of data to obtain valuable business information. In this case, we also have different pricing models based on the number of functions purchased, a fixed monthly rate, a freemium plan or quote-based pricing.
Having a data warehouse requires a proper team of experts to manage it. Such people can fulfil various roles, the most common in this case is the IT Systems Administrator, Database Administrator/Architect, Backend Developer and Data Analyst. Depending on the needs, the team may be larger and consist of many additional roles. All these people will need to be paid, so the expenses, in this case, depending on the size of the team, market rates and often the scope of work.
How expensive is a data warehouse?
Data warehouse pricing depends on the factors that we described above. So if you decide to set up your data warehousing system from off the shelf solutions, you need to choose its components. The most important thing is the actual data warehouse software. Here are examples of the most popular cloud-based data warehouses.
A solution by Google, BigQuery is a fully managed, serverless cloud data warehouse that enables scalable data analysis. It is a Platform as a Service that supports queries using ANSI SQL, and it also has built-in machine learning capabilities. Google BigQuery pricing consists of Analysis Pricing and Storage Pricing. The first is the cost of processing queries, including SQL queries, user-defined functions, scripts, some data manipulation language (DML) statements, etc. Storage pricing is the cost to store data that you load into BigQuery. BigQuery offers two pricing models to run queries – on-demand pricing, in which you are charged for the number of bytes processed by each query, and the first 1 TB of query data processed per month is free. The second option is flat rates, and it assumes you are buying dedicated computing power that you can use to run queries. Currently, the flat-rate monthly cost for 100 slots is $2,000.
Amazon Redshift is part of the larger cloud computing platform Amazon Web Services. It is a data warehouse built on ParAccel’s Mass Parallel Processing (MPP) technology for large-scale datasets and database migration. Redshift allows up to 16 petabytes of data per cluster and also offers various payment models. Charges start at $ 0.25 per hour on-demand, scaling to petabytes of data and thousands of concurrent users. Other models available are Spectrum pricing that allows you to run SQL queries against exabytes of data in AmazonS3 directly, Concurrency Scaling, managed storage pricing and Reserved Instance pricing.
Microsoft Azure Synapse
Azure Synapse is an analytics service that combines data integration, enterprise data warehousing, and big data analytics. Enables you to acquire, explore, prepare, manage, and share data for instant business intelligence and machine learning. Provides high performance, offers many advanced security and privacy features.
It is a modern data warehouse in the cloud with a separate architecture of mass storage and computing. It is part of the comprehensive Snowflake platform for data management, analysis, storage and research. It provides dedicated computing resources. The basic unit of computation here is the virtual data warehouse. The available payment models are for On-demand Storage, Capacity Storage, as well as four models with a different range of functionalities, ranging from Standard, Enterprise, Business Critical and Virtual Private Snowflake.
You can also opt for local storage and choose the on-premises approach. In this case, you also have a lot of software available on the market.
IBM® Integrated Analytics System
The product contains an efficient hardware platform and an optimised database query engine that supports various data analysis and business reporting functions. The IAS software consists of the Db2® Warehouse, which runs in a Docker container and gives control over data and analytical applications, and the IAS software platform, which is responsible for managing and monitoring the hardware components. However, IBM’s offer shows that the emphasis on the transition to the cloud is growing. Hence Db2 Warehouse is also available on the cloud.
Oracle Autonomous Data Warehouse
Oracle offers a fully managed database tuned and optimised for data warehouse workloads. It also provides performance similar to Oracle Database. It is available on-premises, but also like the competition, keeping up with the trends, it offers cloud services and a hybrid option.
Prices for BI and ETL solutions vary by vendor and also increase as you expand your functionality. It is estimated that you need to spend around $ 3,000 annually for the cheapest, basic software option. In addition, there are staff costs, which represent the most considerable expense for data warehouse costs. The four specialists that we wrote about earlier are from about $ 35,000 upwards per month. Therefore, the price of the whole is strongly dependent on the individual choices of components that make up the data warehousing system. Roughly speaking, this is a cost starting at around $ 40,000 per month. However, do not be so influenced by this amount because you should be guided primarily by your business needs. So it may turn out that this amount will be much smaller, or that in your case, custom data warehouse software development is a better solution, which costs are different.
Cloud data warehouses seem to be taking over the market and dominating the local approach. The multitude of available data warehousing solutions makes the selection of appropriate elements for the entire system a time-consuming process that requires reflection. Nevertheless, once everything is fine-tuned, the data warehouse will be of great benefit to the company. It can significantly improve performance and effectiveness, and the introduction of advanced analytics tools will provide insight into previously unknown conclusions that will translate into company profits. It is also an innovative tool to create a uniform, central database that unifies all smaller units in the enterprise. The cost of a data warehouse is very individual, so start by considering your requirements and the system’s needs. Consider the functions, scalability, and human resources you need. If you do not find the solutions available on the market that will fully cover these needs, you can always develop your own software. If you would like a dedicated solution for your business, please do not hesitate to contact BinarApps.