HBase vs Microsoft SQL Server: What are the differences?

# Introduction
This Markdown code discusses the key differences between HBase and Microsoft SQL Server.

1. **Data Model**: HBase follows a column-oriented data model where data is stored in a column-family format, while Microsoft SQL Server uses a row-oriented data model where data is stored in rows and columns within tables.
2. **Scaling**: HBase is designed to handle massive amounts of data and easily scales horizontally by adding more nodes to the cluster, whereas SQL Server is typically scaled vertically by adding more resources to a single server.
3. **Consistency**: HBase provides eventual consistency, where data may not be immediately consistent across all nodes in a cluster, while SQL Server offers strong consistency where data is always up-to-date and consistent across all nodes.
4. **Query Language**: HBase uses HBase Shell and HBase API for querying data, which may require more technical knowledge, while SQL Server uses Transact-SQL (T-SQL) for querying, which is more user-friendly and widely used.
5. **Storage**: HBase stores data in HFiles within HDFS (Hadoop Distributed File System), optimized for write-heavy workloads, while SQL Server stores data in data files on disk, suitable for transactional workloads.
6. **ACID Compliance**: HBase is eventually consistent and not fully ACID compliant, while SQL Server provides full support for ACID properties to ensure data integrity in transactions.

In Summary, the significant differences between HBase and Microsoft SQL Server lie in their data models, scalability, consistency, query languages, storage mechanisms, and ACID compliance.