#Mongodb performance vs postgres code#

OnGres is sharing all the information on the tests they ran, why they were selected and the results they found so that anyone can reproduce the results or change parameters and configurations for their own needs.

#Mongodb performance vs postgres code#

All the code used in testing is open source and available on GitLab, so you can independently reproduce and audit these results as well. The benchmark was designed to be reproducible and run on a public cloud, so anyone who wants to compare Postgres and MongoDB can easily do so. Winner: PostgreSQL 11.1Īdditionally, across all benchmark types, OnGres found that as the datasets becomes bigger than the available memory capacity, the Postgres performance advantage grows over MongoDB. For the OLTP test, the industry standard sysbench benchmark was used with Postgres once again coming out on top, performing three times faster than MongoDB on average. This was a surprising finding, given this is MongoDB’s presumed strength! Winner: PostgreSQL 11.1 Online Transaction Processing (OLTP) Compared: PostgreSQL 11.1 and MongoDB 4.0Īdditional testing was conducted on online transaction processing (OLTP) workloads. Interestingly, Postgres demonstrated a performance advantage in a JSON-based online analytical processing (OLAP) test designed specifically to focus on document-based data. Winner: PostgreSQL 11.1 Online Analytical Processing (OLAP) Compared: PostgreSQL 11.1 and MongoDB 4.0 The Postgres database management system (DBMS) measured between 4 and 15 times faster than MongoDB in transaction performance testing. Given the recent addition of transaction capabilities to MongoDB, it wasn’t too surprising to see a win for Postgres in this one, but the magnitude of the difference was still impressive. Transaction Processing Compared: PostgreSQL 11.1 and MongoDB 4.0 You can find the detailed results in a nearly 50 page white paper available here, but here are a few of the highlights of what he discovered. Horses ready! What was faster, MongoDB or PostgreSQL? His team worked over a 5-month period to evaluate the performance of the two systems using three benchmarks: This is why EDB partnered with Alvaro Hernandez, the Founder of OnGres, to evaluate the performance benchmarks comparing PostgreSQL 11.1 and MongoDB 4.0. And performance is often the main deciding factor. Despite the different data models that MongoDB and PostgreSQL expose, many organizations face the challenge of picking either technology.

But the market demands these kinds of comparisons. Benchmarking databases that follow different approaches (relational vs document) is harder still.

It supports full-text search through the PostgreSQL Full-Text Search extension which integrates with Apache Solr.Benchmarking is hard.

This makes it ideal for applications that are processing large volumes of data such as financial transactions or scientific data sets.

It supports large files up to 1 terabyte in size.

This prevents errors from being introduced by partial operation execution and makes recovery after a crash much simpler. A database that is ACID-compliant means that it guarantees transactions will be processed in their entirety or not at all.

ACID-compliant: ACID stands for atomicity, consistency, isolation and durability.PostgreSQL has a number of features that make it more powerful than other open-source databases: It was developed at the University of California, Berkeley, and released in 1996, but it is still actively maintained and developed by its community. PostgreSQL is an open-source relational database management system (RDBMS). Scalability: MongoDB scales out horizontally by adding additional nodes for better performance or adding capacity for more users or data, thus improving the performance and reliability of an application by distributing the load across multiple machines or data centers.This allows organizations to rapidly prototype applications without having to make any changes in their existing data models or applications. Flexibility: MongoDB supports dynamic schemas and rich data types (such as arrays and embedded documents), which makes it easy to evolve your application without changing the database schema.

Additionally, it has a built-in aggregation framework that can handle complex queries efficiently. High Performance: MongoDB provides high performance, with up to 10K operations per second per node, even on commodity hardware.The following are some of the main features of MongoDB: MongoDB is a popular NoSQL database that many companies have adopted due to its flexibility and scalability. It stores data as JSON documents, making it easier for developers to store and retrieve data. MongoDB is a document-oriented database that provides high performance, high availability, and automatic scaling.