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EDB Postgres AI, the newest PostgreSQL-based database from EnterpriseDB (EDB), outperformed 4 different databases, together with Oracle, SQL Server, MongoDB, and MySQL, on a pair of benchmark exams that span SQL and NoSQL workloads, the seller introduced right this moment.
EDB commissioned McKnight Consulting Group to run a pair of benchmark exams to measure the relative efficiency of EDB Postgres AI towards relational and non-relational databases. McKnight arrange a TPC-C-like take a look at to match the transaction processing prowess of EDB Postgres AI towards Oracle and Microsoft SQL Server, whereas it arrange a JSON processing take a look at to match the multi-modal database towards MongoDB and MySQL, which is managed by Oracle and may course of JSON paperwork.
On the brand new orders per minute (NOPM) transactional take a look at, 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 exams had been carried out on equivalent AWS environments: ixi8xlarge cases operating in US East 1, which price $24,055 per 12 months to run.
The value-per-performance comparisons had been starker. In response to McKnight, EDB Postgres AI was in a position to obtain an NOPM price 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 price 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 assist 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 take a look at. To function the database driver, McKnight used HammerDB, which is “a broadly used and accepted implementation of the TPC-C take a look at,” the corporate says.
A wholly totally different take a look at was used for the JSON workload, however the identical AWS cases had been used. For the JSON take a look at, McKnight used PG NoSQL Benchmark, which is a benchmark software 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.
The take a look at measured how rapidly every database might carry out batch a great deal of JSON paperwork, INSERT the information into the database, after which carry out a SELECT question on the information. The batches ranged from 5 million paperwork (13GB) as much as 100 million paperwork (266GB). The take a look at simulates the kind of database work that may be carried out as a part of a retrieval augmented technology (RAG) pipeline for a generative AI software.
EDB Postgres AI beat the opposite two databases throughout all three JSON exams. For bulk hundreds, EDB was 34% quicker than MongoDB and 63% quicker than MySQL. For database INSERTS, EDB was 4 instances quicker than MySQL and 150 instances quicker than MongoDB. For the SELECT question, EDB was on common nearly 3 instances quicker than MySQL and greater than 5 instances quicker than MongoDB. Extra particulars of the take a look at setup and outcomes may be present in McKnights’ report right here.
The exams pit the world’s 5 hottest databases towards one another. Whereas Oracle, MySQL, and SQL Server proceed to be the most well-liked relational databases, PostgreSQL has emerged to threaten them for dominance, based on DB-Engines rating. MongoDB has been the world’s hottest NoSQL database for nicely over a decade.
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