IT Infrastructure Battlecard: Qlik, Power BI, Tableau

Hello in the next episode of Date with Data. Our TechSavvy company is still searching for the best data&analytics tool for their needs.

They decided to ask Mike Delfino(if you know what fictional character from TV show had that name let me know in the comment??) , their IT Director to look into this three tools from IT infrastructure perspective.

Mike got into work and prepared info. Did he do a good job? Let me know if you agree with the informations he provided, or maybe he made some mistakes in his research?

Objective: Provide an at-a-glance comparison of infrastructure requirements for Power BI, Qlik, and Tableau to support IT decision-making.

Hardware Requirements

Power BI:

- Cloud-Hosted: Primarily Azure-hosted, requires minimal on-premises hardware.

- On-Premises (Power BI Report Server): Requires Windows Server, SQL Server, .NET Framework, minimum of 4 cores CPU, and 8 GB RAM for small deployments.

Qlik:

- Qlik Sense: Can be cloud or on-premises; for the latter, requires multi-core x64 processor, 12 GB RAM.

- QlikView: Requires Windows-based servers, with scaling depending on the size of the data and number of users.

Tableau:

- Tableau Online: Fully hosted, no on-premises hardware needed.

- Tableau Server: Requires at least a dual-core processor and 8 GB RAM for small deployments, scales with data and user base.

Software & Operating System

Power BI:

- Power BI Report Server: Windows Server 2016 or later, SQL Server 2012 Native Client, and IIS support.

Qlik:

- Both QlikView and Qlik Sense run on Windows Server (2012 and later), with Qlik Sense also available on cloud platforms (AWS, Azure, Google Cloud).

Tableau:

- Tableau Server is compatible with Windows Server 2016 or later and Linux (Ubuntu, CentOS), with additional need for PostgreSQL/SQL Server for database management.

Network Considerations

Power BI:

- Requires high bandwidth for cloud services; for on-premises, depends on report complexity and concurrent usage.

Qlik:

- Qlik Sense supports offline data processing, but online services require robust network infrastructure.

Tableau:

- Similar to Power BI, high bandwidth is needed for cloud, with scalability considerations for on-premises setups.

Scalability & Performance

Power BI:

- Highly scalable in the cloud with Azure.

- On-premises scalability is more limited and requires careful planning.

Qlik:

- In-memory technology allows for fast data processing.

- On-premises version requires careful hardware planning for scaling.

Tableau:

- Tableau Server can be scaled by adding more nodes to the cluster.

- Performance is highly dependent on the underlying hardware and network.

Security & Compliance

Power BI:

- Built-in Azure security features, including data encryption and compliance certifications.

Qlik:

- Qlik Sense includes robust security features for data at rest and in transit.

- Compliance with various industry standards, including GDPR.

Tableau:

- Offers comprehensive security features, including user-level security and row-level security.

- Compliance with standards like HIPAA, SOC 2, and GDPR.

Backup & Disaster Recovery

Power BI:

- Azure services include backup and disaster recovery options.

- On-premises requires SQL Server backup procedures.

Qlik:

- Requires manual backup setups for on-premises deployments.

- Cloud versions offer automated backups.

Tableau:

- Tableau Server requires manual backup planning.

- Tableau Online provides automatic backups.

Integration and ecosystem:

Power BI:

- Seamless integration with Azure services and Microsoft products.

- Expansive marketplace for third-party connectors and apps.

Qlik:

- Extensive API support for custom integrations.

- Active community for extensions and connectors.

Tableau:

- Strong connectivity with databases and big data solutions.

- Vast array of third-party data connectors and integrations available.

SUMMARY:

Qlik:

Infrastructure Highlights:

• Flexibility: Offers both on-premises and cloud solutions, with robust support for Windows servers.
• Performance: In-memory technology ensures rapid data processing, but requires substantial server resources for larger datasets.
• Scalability: Scaling requires careful hardware planning, especially for in-memory storage and processing capabilities.

Infrastructure Considerations:

• Backup and Recovery: Manual backup is necessary for on-premises, while cloud versions offer automated solutions.
• Network: Efficient with network resources due to in-memory technology but requires good infrastructure for peak performance.

Power BI:

Infrastructure Highlights:

• Cloud-Native: Primarily designed for cloud with Azure, reducing on-premises infrastructure needs.
• Integration: Seamless integration with Azure services and Microsoft products.
• Lightweight: On-premises version, Power BI Report Server, has modest hardware requirements for small deployments.

Infrastructure Considerations:

• On-Premises Limitations: Larger on-premises installations may need significant hardware investment.
• Network: Cloud services require high bandwidth and low-latency network connections for best performance.

Tableau:

Infrastructure Highlights:

• Versatile: Compatible with Windows and Linux servers, Tableau Server offers flexibility for different IT environments.
• Scalability: Tableau Server scales with the addition of nodes to the cluster, supporting large deployments.
• Data Handling: Efficient at processing large datasets with the right hardware setup.

Infrastructure Considerations:

• Backup and Disaster Recovery: Manual backup procedures are needed for Tableau Server, with no native automated backup solution.
• Performance: Dependent on hardware and can require significant resources for complex visualizations and large user bases.

Thanks for reading! If you have any questions regarding data tools, or you're looking for data&analytics experts, contact me on LinkedIn, I'll do my best to assist you. ?