Microsoft SQL Server is a powerful relational database management system (RDBMS) widely used for enterprise applications. As each version introduces new features, improvements, and fixes, understanding these changes can help businesses make informed decisions. This article dives into the major differences and enhancements in SQL Server 2014, 2016, 2017, and 2019 Release Candidate (RC).
SQL Server 2014: Foundation of Modern Data Management
Released in April 2014, SQL Server 2014 built upon the solid framework of its predecessor, SQL Server 2012. Its key focus was performance improvement, particularly for in-memory processing.
Key Features:
- In-Memory OLTP: Enhanced transaction processing speed by allowing select tables to reside in memory.
- Buffer Pool Extension: Used SSDs to extend RAM and improve read performance for large datasets.
- AlwaysOn Enhancements: Added support for up to eight secondary replicas, improving availability.
Limitations:
- Lacked advanced analytics tools and native JSON support.
- Basic Machine Learning integration was missing.
SQL Server 2016: Enhanced Security and Performance
Released in June 2016, SQL Server 2016 introduced significant advancements in security, analytics, and hybrid cloud capabilities.
Key Features:
- Always Encrypted: Protected sensitive data with encryption at rest and in transit.
- PolyBase: Integrated SQL Server with Hadoop and Azure Blob storage for seamless big data queries.
- Row-Level Security (RLS): Allowed fine-grained access control for rows in a table.
- Temporal Tables: Simplified historical data analysis by tracking changes over time.
- Dynamic Data Masking (DDM): Prevented unauthorized users from viewing sensitive data.
Improvements:
- Performance improvements with Query Store and In-Memory OLTP enhancements.
- Full integration with Microsoft Power BI for advanced data visualization.
SQL Server 2017: Cross-Platform Compatibility
Released in October 2017, SQL Server 2017 broke new ground by introducing support for Linux and containerization. It was also the first version to introduce AI and Machine Learning capabilities.
Key Features:
- Cross-Platform Support: Ran on Windows, Linux, and Docker containers.
- Graph Database Capabilities: Simplified modeling and querying of complex relationships using nodes and edges.
- Python Integration: Built-in support for Python enabled advanced analytics and machine learning.
- Adaptive Query Processing: Improved query performance through real-time execution plan adjustments.
Advantages:
- Broader deployment options for diverse IT environments.
- Enhanced support for AI-driven applications.
SQL Server 2019 RC: Unified Big Data Platform
The Release Candidate (RC) of SQL Server 2019 represented a significant leap forward with features designed for modern data workloads, including big data integration and enhanced analytics.
Key Features:
- Big Data Clusters: Combined SQL Server, Apache Spark, and HDFS to handle large-scale analytics.
- Intelligent Query Processing: Included enhancements like batch mode on rowstore and scalar UDF inlining.
- Data Virtualization: Enabled querying of external data sources without data movement.
- Java Integration: Provided built-in support for Java code execution.
Notable Improvements:
- Superior performance for analytical and transactional workloads.
- Deeper integration with Kubernetes for cloud-native deployments.
Version Comparison Table
| Feature | SQL Server 2014 | SQL Server 2016 | SQL Server 2017 | SQL Server 2019 RC |
|---|---|---|---|---|
| In-Memory OLTP | ✔ | ✔ Improved | ✔ Improved | ✔ Advanced |
| Always Encrypted | ❌ | ✔ | ✔ | ✔ |
| Cross-Platform Support | ❌ | ❌ | ✔ | ✔ |
| Big Data Clusters | ❌ | ❌ | ❌ | ✔ |
| AI and Machine Learning | ❌ | ❌ | ✔ Python | ✔ Python, Java |
| Data Virtualization | ❌ | ❌ | ❌ | ✔ |
| Intelligent Query Processing | ❌ | ❌ | ✔ Basic | ✔ Advanced |
Which Version Should You Choose?
The right SQL Server version depends on your specific needs:
- SQL Server 2014: Suitable for businesses seeking a cost-effective solution for basic OLTP tasks.
- SQL Server 2016: Ideal for organizations prioritizing security and hybrid cloud capabilities.
- SQL Server 2017: Best for companies needing cross-platform support and basic AI tools.
- SQL Server 2019 RC: Recommended for enterprises managing big data workloads or requiring advanced analytics.
Conclusion
Microsoft SQL Server has evolved significantly from 2014 to 2019 RC, offering features tailored for modern workloads. By understanding the strengths of each version, businesses can select the one that aligns with their goals, ensuring better performance, security, and scalability.