Google Cloud Spanner vs HBase: What are the differences?

Google Cloud Spanner vs. HBase:

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1. **Data Model**: Google Cloud Spanner uses a relational data model, allowing for structured data with SQL-like queries, while HBase follows a non-relational model with key-value pairs, ideal for unstructured or semi-structured data storage.
2. **Consistency**: With Google Cloud Spanner, strong consistency is maintained across all distributed transactions, ensuring data integrity, whereas HBase offers eventual consistency, which may lead to inconsistencies in data at times.
3. **Scalability**: Google Cloud Spanner is globally distributed with built-in scalability features, offering automatic sharding and replication across regions, while HBase requires manual configuration for sharding and replication, making it less flexible in terms of scaling.
4. **Performance**: Google Cloud Spanner is optimized for OLTP workloads with low-latency transactions, suitable for real-time applications, while HBase is designed for batch processing and analytical workloads, providing high throughput for big data processing.
5. **Secondary Indexes**: Google Cloud Spanner supports secondary indexes out-of-the-box, enabling efficient querying on non-primary keys, whereas HBase lacks built-in support for secondary indexes, requiring additional workarounds for efficient querying on non-key fields.
6. **Consistency Model**: Google Cloud Spanner offers external consistency, where reads are always consistent and up-to-date with the most recent write, while HBase offers eventual consistency, which may result in stale reads in distributed environments.

In Summary, Google Cloud Spanner and HBase differ in their data models, consistency levels, scalability options, performance characteristics, support for secondary indexes, and consistency models.