HBase vs MongoDB

Bigtable's open-source cousin meets the database for when you want to store json and pretend it's a schema. Here's our take.

HBase

Nice Pick

Bigtable's open-source cousin. Great for massive, sparse data if you don't mind wrestling with Hadoop.

Pros

• Massive scalability on Hadoop HDFS
• Real-time random read/write access to petabytes
• Strong consistency and fault tolerance
• Sparse data storage without wasted space

Cons

• Steep learning curve with complex Hadoop ecosystem dependencies
• Poor performance for small datasets or complex queries

MongoDB

The database for when you want to store JSON and pretend it's a schema.

Pros

• Flexible schema allows rapid prototyping and iteration
• Native JSON-like document storage fits well with modern web apps
• Horizontal scaling with sharding is straightforward
• Aggregation pipeline is powerful for complex queries

Cons

• Lack of enforced schema can lead to messy data over time
• Joins are clunky compared to relational databases

The Verdict

Use HBase if: You want massive scalability on hadoop hdfs and can live with steep learning curve with complex hadoop ecosystem dependencies.

Use MongoDB if: You prioritize flexible schema allows rapid prototyping and iteration over what HBase offers.

The Bottom Line

HBase wins

Bigtable's open-source cousin. Great for massive, sparse data if you don't mind wrestling with Hadoop.