8/25/2023 0 Comments Mongodb or postgresqlYugabyteDB has 2 logical layers – Yugabyte Query Layer and DocDB. So, what’s inside a YugabyteDB node? Let’s look at it from both the logical and physical perspectives. Typically, the term node is used to refer to a single machine in the cluster. In production, YugabyteDB is deployed over a cluster of multiple machines that may be virtual, physical or containerized. If you are unfamiliar with the Yugabyte database, this blog post will help you grasp the key architectural concepts in YugabyteDB by drawing comparisons to PostgreSQL and MongoDB. These include auto sharding, fault tolerance, low read latencies, and support for flexible schema designs using JSON documents. It combines the best features of a SQL database, such as PostgreSQL-compatibility, ACID transactions, relational modeling with JOINS, secondary indexes, and schemas with the characteristics typically found in NoSQL systems. YugabyteDB is a fully open-source distributed SQL database designed for internet-scale, geo-distributed applications. Luckily, YugabyteDB offers a solution by providing a new distributed SQL database with a familiar programming and architectural model, eliminating the complexities. Each database has its own unique terminology and nuances, making the learning process daunting. However, selecting the right database can be challenging due to the numerous niche options available. The testing methodology and results are available here for download.Developing a distributed application or expanding an existing one with new microservices often requires data storage in a distributed database. The tests show that If you want a database that delivers great performance and low latency, you want Postgres. If this was a horse race, Postgres would win by a mile. 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. 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.
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