Data warehouses and data lakes both store massive amounts of data. However, there are several key differences. Understanding what they are, as well as the pros and cons of each, will help you make the right decision for your business. Here’s a simple guide outlining distinctions between the two, as well as the various data lake and data warehouse services available.
Key Differences Between Data Warehouses and Data Lakes
A key difference between data warehouses and data lakes is the type of data they contain. Data lakes are vast pools of raw, unprocessed data. They retain data from multiple sources and support all data types. Data warehouses, on the other hand, contain refined, processed data from pre-approved sources. Everything is neatly archived and ordered in a manner specified by internal resources or data warehouse solution providers.
Another key difference is the purpose of the data, or the lack thereof. In data warehouses, each piece of data has a pre-determined purpose. For example, it’s necessary for reporting or answers an important business question. This isn’t true of data lakes where raw data goes in whether or not a data warehousing consultant or internal resource has identified a use for it.
Top data warehousing companies include Teradata, Oracle, Amazon Web Services (AWS), and Cloudera. Top data lake companies include HVR, Podium Data, Snowflake, and Zaloni. Some businesses also opt for Data-Warehouse-as-a-Service.
Pros and Cons
Because the data in data warehouse solutions is refined and processed, it’s accessible to many users and relatively simple to decipher. This is important to businesses that need to make their data widely available. In comparison, extracting valuable insights from the raw, unprocessed data found in data lakes often requires the expertise of data scientists.
Unlike data lakes which store data that may be never be used, data warehouses only store processed data with a defined purpose. This can result in significant storage savings as businesses only pay to store the data they need.
Processing time and flexibility
The data points stored in data lakes are raw and unprocessed, so users get results more quickly than they do with data warehouses. Data lakes are also more flexible because data warehouses can only provide insights for pre-defined purposes using pre-approved data. Therefore, making changes requires a lot of time and effort. However, data warehouse solution providers may be able to minimize this issue.
Data warehouse security is generally more advanced than data lake security for the simple reason that data warehouses have been around longer. And because data lakes contain a vast pool of data, all in one place, they’re more vulnerable to security threats. To properly secure data lakes, businesses must apply authentication, access controls, and data encryption, or hire a solution provider to do it for them.
How to Decide Between a Data Warehouse and a Data Lake
So, what is the better option, a data lake or a data warehouse? It depends on what you’re trying to achieve. For businesses that need their data to be flexible or agile, data lakes may be best. For organizations that need to contain storage costs or make their data accessible to many people, data warehouses may win out. However, you don’t have to choose just one. Many businesses, particularly those with an established data warehouse, set up a complementary data lake to enjoy the benefits of both.
No matter which method you choose, you don’t have to do it alone. If you’re going the warehouse route, a data warehousing consultant can help. Additionally, many data warehousing companies offer services that can help you get the most from your data. Delivered by trained and experienced experts, data warehouse solutions include everything from design and development to outsourced support. You can even opt for Data-Warehouse-as-a-Service, an outsourcing model that allows you to pay a service provider to configure and manage a data warehouse for you. You just provide the data! Interested in creating a data lake? In addition to data warehouse services, many providers also offer data lake services and support. Data-Lake-as-a-Service is also available.
Hiring the right data warehouse solution provider or a data lake consultant is critical to your success. Before you decide on a method or provider, take time to identify your goals and then partner with a company that can help you achieve them.