Below is a performance comparison of MongoDB to HarperDB.
To see a feature comparison click here.
First, let us state that we are grateful for MongoDB and know that it is a product loved and used by many. MongoDB paved the way for companies like HarperDB to exist and pioneered a new way for developers and users to interact with their data. Without awesome products like MongoDB there would be no HarperDB.
We built HarperDB from the ground up to expand and blend the capabilities of SQL, NewSQL, and NoSQL products like MongoDB because we felt there were certain use cases that could be better served with another solution. We believe that providing developers with the ability to choose the right tool for the job empowers developers and spurs innovation. Some examples where we feel that HarperDB is a better fit include cases where you might need NoSQL and SQL, rapid application development, integration, edge computing, distributed computing, and real-time operational analytics.
As a result, with the release of HarperDB 2.0, we wanted to see how we stacked up against the most popular NoSQL database in the world, MongoDB. Turns out, we’re faster, not just sort of faster much faster.
We asked an external technology team, Mycos Technologies, to create a simple benchmark for HarperDB compared against a modern, accessible, developer centric database, MongoDB. We believe HarperDB is easier to use and provides more flexibility than MongoDB. In this benchmark, we intend to prove that HarperDB holds up performance-wise as well.
HarperDB is 37.9 times faster than MongoDB on average.
HarperDB is up to 98 times faster than mongoDB on reads.
HarperDB is up to 20 times faster than mongoDB on writes.
HarperDB scales out-of-the-box for concurrent operations.
This benchmark evaluates data writes, data reads, and a combination of reads and writes on HarperDB and MongoDB. Tests were executed on both databases using their default configurations. Benchmarks were executed based on recommended benchmarking best practices for both databases. The benchmark tests were executed using Apache JMeter for 10 minutes, with a 10-second ramp up, with a simulated user count of 1, 10, and 50.
The following tests were executed on both databases:
/write data with 1 user
/read data with 1 user
/read/write data with 1 user
/write data with 10 users
/read data with 10 users
/read/write data with 10 users
/write data with 50 users
/read data with 50 users
/read/write data with 50 users
Each test was run two times and using the following order of operations:
1. Create Schema/table for HarperDB or database/collection for MongoDB
2. Loop test action for 10 minutes. Test actions:
a. Write a single, randomly generated record to the database
b. Read a single, randomly selected record from the database
c. Write a single, randomly generated record to the database, then read a single randomly generated record from the database
3. Clean environment
Finding compatible connection patterns for MongoDB is a little tricky, HarperDB uses a rest API, and many other databases rely on product specific drivers and/or an Object Relation Modeling (ORM) library. The initial implementation of this benchmark used Rest Heart, an API front end for MongoDB. The result were not in the competitors favor, therefore it was decided to choose an alternative method provided by BlazeMeter, a leading test automation framework.
A REST API is the primary method to interact with HarperDB. User sessions are not used as each call requires an authorization token. HarperDB was benchmarked via JMeter’s default REST API execution option.
JSR 223 scripting, the accepted scripting language for Java, was used to execute MongoDB connectivity. JMeter was updated with a more current Java driver for MongoDB, version 3.12.3.
In all tests, object data was generated with the following 7 attributes:
Read tests requested a single record from a query request filtering on a random ID value
This benchmark shows that HarperDB is faster than MongoDB in every benchmark test. While HarperDB shows significant advantages in all tests, two cases show a clear distinction: Data reads and concurrent interactions.
Our goal in developing HarperDB was to build a product that would empower developers through ease of use while remaining highly scalable, which we have demonstrably shown in the results of this benchmark. As a result, it was our decision that both databases were benchmarked using default configurations and best practices for both products. HarperDB is built to be simple to install and use, without requiring costly product experts for tuning. We feel that this test conclusively demonstrates that at scale with numerous clients, HarperDB is more performant and can be scaled out more simply and cost-effectively.
Questions, Comments, or feedback? Email us at benchmarks@harpedb.io
Ready to ditch MongoDB? Use code BYEMONGO when signing up for HarperDB Cloud and receive $300 in credits towards our paid tiers.
