By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics in sports industry
    Here’s How Data Analytics In Sports Is Changing The Game
    6 Min Read
    data analytics on nursing career
    Advances in Data Analytics Are Rapidly Transforming Nursing
    8 Min Read
    data analytics reveals the benefits of MBA
    Data Analytics Technology Proves Benefits of an MBA
    9 Min Read
    data-driven image seo
    Data Analytics Helps Marketers Substantially Boost Image SEO
    8 Min Read
    construction analytics
    5 Benefits of Analytics to Manage Commercial Construction
    5 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: Differentiating Between Data Lakes and Data Warehouses
Share
Notification Show More
Latest News
data analytics in sports industry
Here’s How Data Analytics In Sports Is Changing The Game
Big Data
data analytics on nursing career
Advances in Data Analytics Are Rapidly Transforming Nursing
Analytics
data analytics reveals the benefits of MBA
Data Analytics Technology Proves Benefits of an MBA
Analytics
anti-spoofing tips
Anti-Spoofing is Crucial for Data-Driven Businesses
Security
ai in software development
3 AI-Based Strategies to Develop Software in Uncertain Times
Software
Aa
SmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Lake > Differentiating Between Data Lakes and Data Warehouses
Data Lake

Differentiating Between Data Lakes and Data Warehouses

When comparing data lake vs. data warehouse, it's important to know that these two things actually serve quite different roles. They manage data differently and serve their own types of functions.

Liraz Postan
Last updated: 2022/10/20 at 8:23 PM
Liraz Postan
7 Min Read
data lake vs data warehouse
Shutterstock Licensed Photo - By cybrain | stock photo ID: 306988172
SHARE

The market for data warehouses is booming. One study forecasts that the market will be worth $23.8 billion by 2030. Demand is growing at an annual pace of 29%.

Contents
Data LakeData WarehouseData TypeUnderstand the Significance of Data Warehouses and Data Lakes

While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes.

Both data warehouses and data lakes are used when storing big data. On the other hand, they are not the same. A data warehouse is a storage area for filtered, structured data that has been processed already for a particular use, while Data Lake is a massive pool of raw data and the aim is still unknown.

Many people are confused about these two, but the only similarity between them is the high-level principle of data storing.  It is vital to know the difference between the two as they serve different principles and need diverse sets of eyes to be adequately optimized. However, a data lake functions for one specific company, the data warehouse, on the other hand, is fitted for another.

More Read

data analytics in sports industry

Here’s How Data Analytics In Sports Is Changing The Game

What Role Does Big Data Have on the Deep Web?
Use this Strategic Approach to Maximize Your Data’s Value
How Data and Smart Technology Are Helping Hospitalists
Niche Data Tactics to Take Your Business to the Next Level

This blog will reveal or show the difference between the data warehouse and the data lake. Below are their notable differences.

Data Lake

  • Type of Data: structured and unstructured from different sources of data
  • Purpose: Cost-efficient big data storage
  • Users: Engineers and scientists
  • Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning
  • Sizes: Store data which might be utilized

Data Warehouse

  • Data Type: Historical which has been structured in order to suit the relational database diagram
  • Purpose: Business decision analytics
  • Users: Business analysts and data analysts
  • Tasks: Read-only queries for summarizing and aggregating data
  • Size: Just stores data pertinent to the analysis

Data Type

Data cleaning is a vital data skill as data comes in imperfect and messy types. Raw data that has not been cleared is known as unstructured data; this includes chat logs, pictures, and PDF files. Unstructured data that has been cleared to suit a plan, sort out into tables, and defined by relationships and types, is known as structured data. This is a vital disparity between data warehouses and data lakes.

Data warehouses contain historical information that has been cleared to suit a relational plan. On the other hand, data lakes store from an extensive array of sources like real-time social media streams, Internet of Things devices, web app transactions, and user data. This data is often structured, but most of the time, it is messy as it is being ingested from the data source.

  • Purpose

When it comes to principles and functions, Data Lake is utilized for cost-efficient storage of significant amounts of data from various sources. Letting data of whichever structure decreases cost as it is flexible as well as scalable and does not have to suit a particular plan or program. On the other hand, it is easy to analyze structured data as it is cleaner. It also has the same plan to query from. A data warehouse is very useful for historical data examination for particular data decisions by limiting data to a plan or program.

You might see that both set off each other when it comes to the workflow of the data. The ingested organization will be stored right away into Data Lake. Once a particular organization concern arises, a part of the data considered relevant is taken out from the lake, cleared as well as exported.

  • Users

Each one has different applications, but both are very valuable for diverse users. Business analysts and data analysts out there often work in a data warehouse that has openly and plainly relevant data which has been processed for the job. Data warehouse needs a lower level of knowledge or skill in data science and programming to use.

Engineers set up and maintained data lakes, and they include them into the data pipeline. Data scientists also work closely with data lakes because they have information on a broader as well as current scope.

  • Tasks

Engineers make use of data lakes in storing incoming data. On the other hand, data lakes are not just restricted to storage. Keep in mind that unstructured data is scalable and flexible, which is better and ideal for data analytics. A big data analytic can work on data lakes with the use of Apache Spark as well as Hadoop. This is true when it comes to deep learning that needs scalability in the growing number of training information.

Usually, data warehouses are set to read-only for users, most especially those who are first and foremost reading as well as collective data for insights. The fact that information or data is already clean as well as archival, usually there is no need to update or even insert data.

  • Size

When it comes to size, Data Lake is much bigger than a data warehouse. This is because of the fact that Data Lake keeps hold of all information that may be pertinent to a business or organization. Frequently, data lakes are petabytes, which is 1,000 terabytes. On the other hand, the data warehouse is more selective or choosy on what information is stored.

Understand the Significance of Data Warehouses and Data Lakes

If you are settling between data warehouse or data lake, you need to review the categories mentioned above to determine one that will meet your needs and fit your case. In case you are interested in a thorough dive into the disparities or knowing how to make data warehouses, you can partake in some lessons offered online.

Always keep in mind that sometimes you want a combination of these two storage solutions, most especially if developing data pipelines.

Written by: Rudderdstack.com, Segment alternative

TAGGED: big data, data lake, data warehouse
Liraz Postan September 23, 2020
Share this Article
Facebook Twitter Pinterest LinkedIn
Share
By Liraz Postan
Follow:
Liraz is an international SEO and content expert, helping brands and publishers grow through search engines. She is Outbrain's former SEO and Content Director and previously worked in the gaming, B2C and B2B industries for more than 13 years.

Follow us on Facebook

Latest News

data analytics in sports industry
Here’s How Data Analytics In Sports Is Changing The Game
Big Data
data analytics on nursing career
Advances in Data Analytics Are Rapidly Transforming Nursing
Analytics
data analytics reveals the benefits of MBA
Data Analytics Technology Proves Benefits of an MBA
Analytics
anti-spoofing tips
Anti-Spoofing is Crucial for Data-Driven Businesses
Security

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

data analytics in sports industry
Big Data

Here’s How Data Analytics In Sports Is Changing The Game

6 Min Read
big data technology has helped improve the state of both the deep web and dark web
Big Data

What Role Does Big Data Have on the Deep Web?

8 Min Read
analyzing big data for its quality and value
Big Data

Use this Strategic Approach to Maximize Your Data’s Value

6 Min Read
big data and smart technology in healthcare
Big Data

How Data and Smart Technology Are Helping Hospitalists

8 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US

© 2008-23 SmartData Collective. All Rights Reserved.

Removed from reading list

Undo
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?