Many use the terms “data lake” and “data warehouse” interchangeably, but there are actually some key differences. The distinction is especially important if you’re thinking about hiring a development company to build a custom data lake for your business.

Data Lake versus Data Warehouse

Big data storage platforms can bring lots of benefits, but only if you build a platform that suits your exact needs. These points should be carefully considered before you choose to leverage one (or both) of these platforms.  

What is a Data Lake?   

A data lake is a vast data storage area containing raw, unstructured data that has not been filtered or processed in any way. It’s common for a company to configure multiple data streams so they feed directly into the data lake. That data lake can then be tagged and subsequently queried in a manner that allows users to pull out the data they need for a particular purpose.   

In fact, it’s common for a data lake to be structured with multiple user roles, each with a unique degree of access and permissions. This is essential for maintaining security and organization. Limiting data lake access is also important for maintaining the integrity of a data lake. Raw data could easily be lost if an inexperienced user were to move the data or modify the tagging.   

What is a Data Warehouse?   

A data warehouse may be used in combination with a data lake, as this storage platform contains already-filtered and structured data. If you were to pull a specific data set for a report, this data would be shifted into a data warehouse since it has been processed and filtered from its raw state.    

Data warehouses store data that has been modified from its raw, original state. But there are many times when a single data set can be leveraged in different ways, by different divisions of a company. This is why it’s useful to retain a copy of the raw data in a data lake environment. This is one way in which you can use both a data lake and a data warehouse in tandem.   

Data Warehouse vs. Data Lake: Which is Better? 

Both data storage options have their own pros and cons. The best option will vary according to your exact needs. A data warehouse may be a good choice if you have a firm understanding of the data you need to retain for future use. All other data can be discarded, cutting down on the amount of storage space that’s required. Otherwise, you may want to utilize a data lake and a data warehouse in tandem—one as a data reservoir and one to hold usable data that fuels data analysis.

Conversely, many companies have a plethora of potential uses for their data. It would be impossible to predict which bits of information may be useful in the future. For this type of company, a data lake could be the better choice, even if that means storing a far larger volume of data. Notably, with today’s scalable cloud solutions, data storage costs are lower than ever before. More and more companies are opting to retain most or all of their raw data in a data lake environment.

Traditionally, many have moved toward data warehouses instead of data lakes due to the ease of navigating a warehouse environment. There are inherent challenges associated with handling large volumes of raw, unprocessed data. Until recently, companies needed a seasoned data analyst or data scientist on-staff to make full use of a data lake. That’s not necessarily true of today’s modern data lakes, which can include tagging capabilities and a robust querying function.

In fact, you can utilize powerful data lake development software like Sertics, a SevenTablets product. With Sertics, you can proceed with confidence, knowing that our big data developers can create a platform that will meet your company’s unique needs and objectives. If you need a data lake that’s navigable by and accessible to a broad range of staff, we’ll work with you to gain an understanding of your needs. Then, we’ll craft a custom data lake environment that will provide the maximum benefit for your business.

At SevenTablets, we take great pride in our approach to big data, custom software development and mobile app development. We believe that every platform should feature well-architected software, with an intuitive, user-friendly UI/UX. Our specialties include more than just big data; we also specialize in a range of other technologies such as Predictive Analytics (PA) and Artificial Intelligence (AI).

SevenTablets is headquartered in Dallas, with additional regional offices located in Houston and Austin, Texas. We work with clients spanning the nation and beyond, so if you’re seeking to build a custom data lake or other custom solution for your business, reach out to the team at SevenTablets today.  

Reach out to our team today!

Anand Balasubramanian

Anand Balasubramanian

Chief Technology Officer at SevenTablets
Anand has been a technology executive for more than a decade with a deep background in driving the alignment of government, business and information. He has broad experience building revenue-generating products and services through a hands-on approach. Anand was also a delivery leader for Secretary of State solutions in the U.S. He earned his Master's of Computer and Information Science from the University of Madras in '98.
Anand Balasubramanian