Connection pool

In software engineering, a connection pool is a cache of database connections maintained so that the connections can be reused when future requests to the database are required. ^[1] Connection pools are used to enhance the performance of executing commands on a database. Opening and maintaining a database connection for each user, especially requests made to a dynamic database-driven website application, is costly and wastes resources. In connection pooling, after a connection is created, it is placed in the pool and it is used again so that a new connection does not have to be established. If all the connections are being used, a new connection is made and is added to the pool. Connection pooling also cuts down on the amount of time a user must wait to establish a connection to the database.

Applications

Web-based and enterprise applications use an application server to handle connection pooling. Dynamic web pages without connection pooling open connections to database services as required and close them when the page is done servicing a particular request. Pages that use connection pooling, on the other hand, maintain open connections in a pool. When the page requires access to the database, it simply uses an existing connection from the pool, and establishes a new connection only if no pooled connections are available. This reduces the overhead associated with connecting to the database to service individual requests.

Local applications that need frequent access to databases can also benefit from connection pooling. Open connections can be maintained in local applications that do not need to service separate remote requests like application servers, but implementations of connection pooling can become complicated. A number of available libraries implement connection pooling and related SQL query pooling, simplifying the implementation of connection pools in database-intensive applications.

Administrators can configure connection pools with restrictions on the numbers of minimum connections, maximum connections and idle connections to optimize the performance of pooling in specific problem contexts and in specific environments.

In Amazon Web Services

In modern cloud architectures like AWS, effective connection pooling management is critical for optimizing performance, scalability, and resource utilization. Improper handling of connections can lead to bottlenecks and operational inefficiencies. Connection pooling behavior varies across compute platforms: ^{[2] [3] [4]}

1. Function-as-a-Service (FaaS): AWS Lambda creates new database connections per invocation, which can cause connection storms under high concurrency if unmanaged. Solutions like Amazon RDS Proxy help pool connections efficiently.
2. Containerized Environments: Amazon Elastic Container Service (ECS) containers maintain open database connections for their lifecycle. Without connection pooling mechanisms (e.g., HikariCP, pgbouncer), idle or excessive connections can strain database resources.
3. Virtual Machine-Based Environments: AWS EC2 instances scale connection demand with the number of instances. Manual or automated tuning of connection pool parameters is essential to prevent exceeding database limits.

Modern cloud databases offer advanced solutions to mitigate connection pooling challenges: ^{[2] [3] [4]}

• AWS Aurora Serverless v2: Dynamically scales connections and abstracts the need for manual connection pooling, ideal for unpredictable workloads.
• AWS DynamoDB: A stateless NoSQL database, eliminates traditional connection pooling, making it inherently scalable and serverless-friendly.

This ecosystem of tools and services empowers architects to design highly scalable and efficient applications while minimizing connection management overhead.

In Microsoft Azure

In Azure Cosmos DB, connection pooling is managed at the SDK level rather than by the database service itself. SDKs such as those for .NET, Java, and Python implement connection pooling to reuse HTTP connections to the database endpoint, optimizing resource usage and performance. This functionality applies to all Cosmos DB account types, including provisioned throughput and serverless models. The stateless, HTTP-based architecture of Cosmos DB facilitates scalable and concurrent operations without the limitations typically associated with traditional connection pooling mechanisms. ^[5]

See also

• Object pool pattern

References

1. Pugh, Eric; Gradecki, Joseph D. (11 November 2005). Professional Hibernate. John Wiley & Sons. p. 65. ISBN   978-0-7645-8951-5 . Retrieved 18 October 2022.
2. Engineering Resilient Systems on AWS. ISBN   9781098162399.
3. Serverless Architectures on AWS, Second Edition. ISBN   9781638354024.
4. Developing Modern Database Applications with PostgreSQL: Use the highly available and object-relational PostgreSQL to build scalable and reliable apps. ISBN   9781838641061.
5. Cosmos DB for MongoDB Developers: Migrating to Azure Cosmos DB and Using the MongoDB API. ISBN   9781484236826.

External links

• "Properly Handling Pooled JDBC Connections", blog post by Christopher Schultz