Altoros Releases 2020 Comparative Analysis Report of NoSQL Databases as a Service: Couchbase Cloud, MongoDB Atlas, and AWS DynamoDB

A new study by Altoros analyzes the query performance of three database languages using Yahoo! Cloud Serving Benchmark and custom tests

Altoros, a consultancy focusing on research and development for Global 2000 organizations, today announced the results of its latest performance benchmark report. The study provided a comparative analysis of Couchbase Cloud, MongoDB Atlas, and AWS DynamoDB on three different cluster configurations (6, 9, and 18 nodes) and under four different workloads.

NoSQL databases have complex structures with many components. And frequently, NoSQL cluster deployments become challenging to oversee and manage for engineering teams. To avoid investing increasing amounts of time and money on cluster support, deployment, and maintenance, teams will seek database-as-a-service (DBaaS) alternatives.

The Altoros report measures the relative performance in terms of latency and throughput that each database can achieve. The Yahoo! Cloud Serving Benchmark (YCSB) is an open-source specification and program suite for evaluating retrieval and maintenance capabilities of computer programs. It was used as the default tool for evaluation consistency.

Workloads under pressure

The first workload performs update-heavy activity, invoking 50% reads, and 50% updates of the data. The second workload performs a short-range scan that invokes 95% scans and 5% updates, where short ranges of records are queried instead of individual ones. The third workload, “Pagination,” represents a query with a single filtering option to which an offset and a limit are applied. Finally, the fourth workload is a join query with grouping and ordering applied. Not every product was able to complete these last two exercises.

Different requirements

Altoros defined the database performance of the report by the speed at which a database processed basic operations. The basic operation is an action performed by a workload executor, which drives multiple client threads. Each thread executes a sequential series of operations by making calls to a database interface layer to load a database (the load phase) and execute a workload (the transaction phase).

The threads throttle the rate at which they generate requests so that Altoros can directly control the load against the database. In addition, the threads measure latency and the achieved throughput of their operations and report these measurements to the statistics module.

“Our findings show how hardly any DBaaS can perfectly fit all the requirements of any given use case. Every solution has its advantages and disadvantages that become important in varying degrees, depending on the specific criteria to meet. But fundamentally, DBaaS helps engineers to reduce the time for deployment, configurations, and support,” said Igor Aksinin, Director of Business Development at Altoros.

Download the report here.

About Altoros

Altoros is a 300+ people strong consultancy that helps Global 2000 organizations with a methodology, training, technology building blocks, and end-to-end solution development. The company turns cloud-native app development, customer analytics, blockchain, and AI into products with a sustainable competitive advantage. Visit or follow @altoros.

Source: Altoros


Categories: High Technology

Tags: Couchbase, DynamoDB, MongoDB, NoSQL