Google Cloud Spanner vs Hadoop: What are the differences?

Introduction

Google Cloud Spanner and Hadoop are two popular technologies used for handling big data processing, but they have key differences in terms of data model, scalability, query flexibility, data storage, data consistency, and ecosystem maturity.

1. Data Model: Google Cloud Spanner is a horizontally scalable, globally distributed relational database while Hadoop is a framework for distributed processing of large data sets across clusters of computers. Spanner provides ACID transactions and enforces relational schema, whereas Hadoop does not enforce a schema and is more suitable for unstructured or semi-structured data.

2. Scalability: Spanner is designed for horizontal scalability and can handle large workloads with ease. It automatically splits and distributes data across multiple servers for high availability and performance. Hadoop also scales horizontally by adding more servers to the cluster, but it requires manual configuration and optimization to achieve optimal scalability.

3. Query Flexibility: Spanner supports SQL for querying data, which makes it easy to use for developers familiar with relational databases. Hadoop, on the other hand, supports various query languages like HiveQL, Pig Latin, and Spark SQL, which provide more flexibility for different use cases and data processing needs.

4. Data Storage: Spanner uses a distributed storage system called Colossus for storing its data, providing high durability and availability. Hadoop, on the other hand, can use various storage systems like Hadoop Distributed File System (HDFS), Amazon S3, or Azure Blob Storage, which provides flexibility in choosing the storage solution based on the requirements.

5. Data Consistency: Spanner guarantees strong consistency across all replicas, even in the presence of network partitions or failures. Hadoop's consistency model depends on the underlying storage system used, and it may trade off consistency for scalability or fault tolerance.

6. Ecosystem Maturity: Spanner is a fully managed service provided by Google, which means it has a mature ecosystem with support for various tools and integrations. Hadoop, being an open-source framework, also has a rich ecosystem with a wide range of tools and libraries, but it requires more effort and expertise to set up and manage.

In summary, Google Cloud Spanner is a globally distributed, highly scalable relational database with ACID transactions and strong consistency, while Hadoop is a framework for distributed processing of large datasets with a flexible data model and a rich ecosystem of tools.