Database vs DataMart vs Data Warehouse vs Data Lake

Question

Looking for the high-level differences/comparison among

• Database
• Data Mart (Top-down approach)
• Data Warehouse
• Data Lake
• Data Lakehouse

Please use relative comparison when specifics are not available.

Etymologize

Would it be practical to update this question to also consider the Data Lakehouse? – Hillyer

@ShawnEary - Good one! I updated the question and the answer as well! – Etymologize

Answer 1

Included below is a high-level comparison between the various data tiers mentioned. Please feel free to drop a comment if any of these need corrections.

Feature	Database	Data Mart	Data Warehouse	Data Lake	Data Lakehouse
Source	Single	Single	Multiple	Multiple	Multiple
Structure	Structured	Structured	Structured	Raw	Structured, semi-structured, and unstructured
Purpose	Determined	Determined	Determined	Determined	Determined
Storage	Centralized	Decentralized	Centralized	Centralized	Centralized
Data Format	Detailed	Summarized	Both detailed and summarized	All	All
Flexibility	Low	Medium	Medium	High	High
Primary Use	Transactional	Reporting	Analytics & Reporting	Analytics	Analytics
Cost	Low	Medium	Medium	High	High
Data Volume	Low	Low	Medium	High	High
Development	Top-down	Bottom-up	Top-down	All	All
Design Time	Medium	Medium	High	Low	Low
Volatility	Medium	Low	None	None	None
Data Operations	CRUD	CR	CRU	CR	CRUD
Subject Area	Single	Single	Multiple	Multiple	Multiple
Design Schema	Relational	Multi-dimensional	Relational	No schema	Hybrid

Notes:

• The cost of a data lakehouse can be lower than a data warehouse if the data is stored in a cloud-based object storage system.
• The data volume of a data lake can be much higher than a data warehouse or data mart.
• The development time for a data lakehouse can be lower than a data warehouse if the data is already stored in a cloud-based object storage system.
• The volatility of a data lake can be higher than a data warehouse or data mart because the data is not always structured and may change frequently.

Fit-gap

• If you need a low-cost, flexible repository for structured data, then a database is a good option.
• If you need a repository for summarized data for reporting purposes, then a data mart is a good option.
• If you need a repository for detailed data for analytics and reporting purposes, then a data warehouse is a good option.
• If you need a repository for all types of data for analytics and machine learning purposes, then a data lakehouse is a good option.

Etymologize

Nice answer. You know you can just type a markdown table into your answer, rather than a code snippet with generation and screenshot of that? Anyway, could you please clarify if "design time" is the design of the database, or design of things which use the database? – Berceuse

Thanks @falsePockets. Updated it to Markdown Table :). As for the design time - it's for the design of the datastore, it's infra, layout, clustering, replication, scaling, security, integration mechanisms, etc. – Etymologize