EDB Postgres AI, the most recent PostgreSQL-based database from EnterpriseDB (EDB), outperformed 4 different databases, together with Oracle, SQL Server, MongoDB, and MySQL, on a pair of benchmark checks that span SQL and NoSQL workloads, the seller introduced right now.
EDB commissioned McKnight Consulting Group to run a pair of benchmark checks to measure the relative efficiency of EDB Postgres AI in opposition to relational and non-relational databases. McKnight arrange a TPC-C-like check to check the transaction processing prowess of EDB Postgres AI in opposition to Oracle and Microsoft SQL Server, whereas it arrange a JSON processing check to check the multi-modal database in opposition to MongoDB and MySQL, which is managed by Oracle and also can course of JSON paperwork.
On the brand new orders per minute (NOPM) transactional check, McKnight measured EDB Postgres AI hitting a peak throughput of about 987,000 NOPM in comparison with about 844,000 for Oracle and about 759,000 for SQL Server. The checks have been carried out on equivalent AWS environments: ixi8xlarge situations working in US East 1, which value $24,055 per 12 months to run.
Supply: McKnight Consulting Group
The worth-per-performance comparisons have been starker. In line with McKnight, EDB Postgres AI was capable of obtain an NOPM value of $0.21 per unit in comparison with Oracle’s $1.58 and SQL Server’s $1.26. The variations are because of the larger value of the Oracle ($47,500 per unit) and Microsoft ($15,123 per unit) software program environments in comparison with EDB ($2,780 per unit), in addition to larger help prices ($10,450 per unit for Oracle and $3,327 per unit for Microsoft versus zero for EDB).
McKnight notes that, whereas the NOMP benchmark was arrange in accordance with TPC-C requirements, it was not an official TPC-C benchmark check. To function the database driver, McKnight used HammerDB, which is “a extensively used and accepted implementation of the TPC-C check,” the corporate says.
A completely totally different check was used for the JSON workload, however the identical AWS situations have been used. For the JSON check, McKnight used PG NoSQL Benchmark, which is a benchmark device created by EDB to check PostgreSQL and MongoDB databases. McKnight modified the syntax of the benchmark to incorporate MySQL, which is also able to processing JSON information.
Supply: McKnight Consulting Group
The check measured how shortly every database might carry out batch a great deal of JSON paperwork, INSERT the info into the database, after which carry out a SELECT question on the info. The batches ranged from 5 million paperwork (13GB) as much as 100 million paperwork (266GB). The check simulates the kind of database work that might be carried out as a part of a retrieval augmented era (RAG) pipeline for a generative AI software.
EDB Postgres AI beat the opposite two databases throughout all three JSON checks. For bulk hundreds, EDB was 34% quicker than MongoDB and 63% quicker than MySQL. For database INSERTS, EDB was 4 occasions quicker than MySQL and 150 occasions quicker than MongoDB. For the SELECT question, EDB was on common nearly 3 occasions quicker than MySQL and greater than 5 occasions quicker than MongoDB. Extra particulars of the check setup and outcomes might be present in McKnights’ report right here.
The checks pit the world’s 5 hottest databases in opposition to one another. Whereas Oracle, MySQL, and SQL Server proceed to be the preferred relational databases, PostgreSQL has emerged to threaten them for dominance, in keeping with DB-Engines rating. MongoDB has been the world’s hottest NoSQL database for properly over a decade.
Associated Gadgets:
Microsoft Open Sources Code Behind PostgreSQL-Based mostly MongoDB Clone
Postgres17 Brings Enhancements to JSON, Backup, And Extra
Postgres Rolls Into 2024 with Large Momentum. Can It Hold It Up?