DuckDB and HBase are two data management systems with different characteristics and purposes. Here are the key differences between them:

1. Data Model: DuckDB is a columnar analytical database that is optimized for handling complex queries on large datasets. It stores data in columns rather than rows, allowing for efficient data compression and query performance. On the other hand, HBase is a distributed, scalable, non-relational database that follows a key-value store model. It is designed for storing and managing large amounts of structured and semi-structured data in real-time.

2. Query Language: DuckDB supports standard SQL as its query language, making it easy for users familiar with SQL to interact with the database. HBase, on the other hand, uses HBase Shell, which is a command-line interface that allows users to interact with the database using commands similar to those in SQL, but with some differences and limitations.

3. Data Consistency: DuckDB guarantees strong consistency, meaning that when a write is committed, any subsequent read will see the updated data. HBase, however, provides eventual consistency, which means that there might be a delay before all replicas of the data get updated. This tradeoff in consistency allows HBase to achieve high availability and fault tolerance.

4. Scale and Distribution: DuckDB is not designed for massive scalability or distribution across multiple nodes. It is primarily used for analytical workloads on a single machine or within a small cluster. In contrast, HBase is built for scalability and can handle massive amounts of data across a large number of commodity hardware nodes.

5. Data Storage: DuckDB stores data on disk and leverages compression techniques to optimize storage space. HBase, on the other hand, stores data in a distributed file system like HDFS, breaking it into blocks and distributing it across the nodes in the cluster.

6. Access Patterns: DuckDB is optimized for read-heavy workloads, where complex analytical queries need to be executed efficiently. It provides fast query performance by utilizing columnar storage and various optimizations. HBase, on the other hand, is designed for high-throughput read and write operations, making it suitable for real-time applications that require low-latency data access.

In Summary, DuckDB is a columnar analytical database with strong consistency and a focus on read-heavy workloads, while HBase is a distributed key-value store with eventual consistency, scalability, and suitability for real-time applications.