flowchart LR
A[Choose Database Structure] --> B{Type of Data and Use Case}
%% OLAP Variants
B --> C[Analytical Needs?]
C -->|Yes| D[OLAP Variants]
D --> D1[MOLAP]
D --> D2[ROLAP]
D --> D3[HOLAP]
D1 --> D11[Use if precomputed cubes and fast queries needed]
D2 --> D21[Use if working directly on relational data is preferred]
D3 --> D31[Use if a balance of MOLAP and ROLAP is ideal]
%% Data Lakes
C -->|No| E[Handle Unstructured or Semi-structured Data?]
E -->|Yes| F[Data Lake]
F --> F1[Ideal for IoT, web scraping, large datasets]
%% Real-time OLAP Databases
F -->|No| G[Real-time Analytics?]
G -->|Yes| H[Real-time OLAP Databases]
H --> H1[Low-latency and fast querying, examples include Druid and Pinot]
H --> H2[Streaming databases for continuous data processing, such as RisingWave]
%% NoSQL Databases
G -->|No| I[Flexible Schema?]
I -->|Yes| J[NoSQL Databases]
J --> J1[Document Store like MongoDB for JSON data]
J --> J2[Graph Database like Neo4j for relationship-focused data]
%% In-Memory OLAP
I -->|No| K[Need for High-Speed, In-Memory Processing?]
K -->|Yes| L[In-Memory OLAP]
L --> L1[Ideal for time-sensitive analytics with reduced disk access]
%% Self-Service BI
K -->|No| M[Enable Business User Exploration?]
M -->|Yes| N[Self-Service BI]
N --> N1[Column-store with ad hoc analysis for non-technical users]
%% Cloud-based Analytics (COLAP)
M -->|No| O[Scalability and Cost Efficiency Priority?]
O -->|Yes| P[COLAP]
P --> P1[Scalable, hosted OLAP on cloud platforms]
%% Emerging Paradigms
B -->|Alternative Needs| Q{Emerging Paradigms}
%% Data Lakehouse
Q --> R[Data Lakehouse]
R --> R1[Combines lake and warehouse features for diverse analytics]
%% NewSQL
Q --> S[NewSQL]
S --> S1[Scalable and ACID-compliant, supports OLAP and OLTP]
%% HTAP
Q --> T[HTAP]
T --> T1[Unified transactional and analytical workloads]
%% Data Mesh
Q --> U[Data Mesh]
U --> U1[Distributed ownership, scalable in federated organizations]
%% Multi-Model Databases
Q --> V[Multi-Model Databases]
V --> V1[Supports various data models for flexible applications]
%% Vector Databases
Q --> W[Vector Databases]
W --> W1[Optimized for high-dimensional data in ML and AI]
%% Serverless Databases
Q --> X[Serverless Databases]
X --> X1[Cost-effective with automatic scaling for varying workloads]