Comparing SQL databases with No-SQL databases depends on the specific use case you encounter in your daily workflow. When working with tabular data, a relational database is a better choice. In contrast, if your work requires you to handle semi-structured or unstructured data, No-SQL databases provide an efficient solution.
Among these databases, two popular choices are DynamoDB and PostgreSQL. However, they differ significantly, which might cause confusion when selecting one over the other.
This guide will help you understand the key differences between DynamoDB vs PostgreSQL and select the optimal solution for your daily tasks.
DynamoDB: An Introduction
Offered by Amazon Web Services (AWS), DynamoDB is a serverless, cloud-based NoSQL database service. It enables you to efficiently handle large volumes of semi-structured and unstructured data while providing low latency. Supporting a schema-less architecture, DynamoDB offers flexibility in handling different formats and data structures.
With its fully managed nature, DynamoDB allows you to scale your applications automatically without infrastructure management. This feature is an essential factor that separates this tool from others, especially when you don’t want to spend your time managing the database.
Key Features of DynamoDB
- Multi-active Replication: Global tables provide a multi-active replication feature, allowing you to specify the region where you want high data availability. With this feature, your application can access data locally in the region you select, achieving fast read and write performance.
- ACID Transactions: Unlike many NoSQL databases, DynamoDB complies with atomicity, consistency, integrity, and reliability (ACID) transactions to support mission-critical workloads.
- Secondary Indexes: Using global and local secondary indexes, you can query the data using an alternate key. The secondary indexes can help you access data with attributes other than the primary key, providing you flexibility while accessing data.
- Caching: DynamoDB Accelerator (DAX) is a caching service that delivers up to 10 times performance improvement for millions of requests per second.
- Security: Utilizing AWS identity and access management (IAM), you can manage permissions and control the number of users accessing resources. With advanced security features, including encryption, key management, and fine-grained access control, DynamoDB safeguards your data.
PostgreSQL: An Introduction
PostgreSQL is an open-source object-relational database management system (RDBMS) that enables you to handle structured data in tabular form. Developed by UC Berkley, this platform is compliant with ACID properties to support concurrency and SQL standards. By offering robust plugins like PostGIS, PostgreSQL extends its capabilities to store, index, and query geospatial data.
To efficiently handle increasing workloads, Postgres offers vertical scaling. Vertical scaling requires upgrading the available resources by adding CPU, RAM, and storage to perform intensive tasks. Although PostgreSQL doesn’t natively support horizontal scaling, features like partitioning and replication can help you enhance scalability.
Key Features of PostgreSQL
- Concurrency Control: The multiversion concurrency control (MVCC) feature ensures high concurrency in a multi-user environment. Using this feature, PostgreSQL maintains data integrity and avoids conflicts while performing multiple transactions simultaneously.
- Replication: PostgreSQL offers built-in replication features like streaming and logical replication, which help you enhance data availability through redundancy. In streaming replication, the primary servers send data while the standby servers receive it. For logical replication, the publisher, a data source, replicates data to the subscriber, a data receiver.
- Indexing: With multiple types of indexing, including B-tree, Partial, Expressions, and Multicolumn, PostgreSQL enables you to enhance query performance and provide improved sorting and search capabilities.
- Partitioning: Splitting a large data table into smaller pieces, or partitioning, is an essential feature that can significantly enhance query performance. PostgreSQL supports different partitioning methods, including range, list, and hash partitioning.
- Security: PostgreSQL protects your data from cyberattacks with robust security features, including SSL encryption, role-based access control, LDAP authentication, and row-level security.
DynamoDB vs PostgreSQL: Key Differentiating Factors
Here’s a comparison table that highlights the critical aspects that differentiate Postgres vs DynamoDB.
Let’s explore the detailed attributes that can help you decide between DynamoDB vs PostgreSQL.
Performance
When comparing DynamoDB vs Postgres performance, both tools serve different purposes. If you use DynamoDB to manage relational data operations, it might not be the optimal choice. The same goes for Postgres while handling semi-structured data. However, each tool provides certain features through which you can enhance their individual performance.
DynamoDB offers an in-memory caching feature, or DynamoDB Accelerator (DAX), which enables you to enhance the read capabilities by 10 times. With this feature, you can serve millions of requests per second. Another in-built performance-enhancing technique that DynamoDB utilizes is a request router that decreases time complexity for querying and fetching data.
In contrast, PostgreSQL’s performance will depend on the hardware and the data management technique you use. Beyond the hardware requirements, there are some features that you can utilize to enhance performance. These features include advanced indexing techniques and Just-in-time (JIT) to accelerate query speed.
Scalability
Although both tools, including DynamoDB and PostgreSQL, offer vertical scaling, the difference arises due to horizontal scalability. DynamoDB offers auto-scaling features where the data is automatically partitioned and replicated across multiple available zones. By reducing the manual intervention, this tool allows you to scale read and write capacity based on the workload, offering high availability and durability.
PostgreSQL, on the other hand, doesn’t support horizontal scaling by default. However, features like partitioning and replication provide enhanced scaling capabilities. Partitioning enables you to split larger data into smaller components to enhance storage. In replication, you can copy the data from one node to another to ensure high availability during failures.
Flexibility
Being a NoSQL key-value data model, DynamoDB doesn’t require a predefined schema, providing you the flexibility for handling semi-structured and unstructured data. However, it sacrifices data modeling capabilities, as it doesn’t support functions that allow you to build custom logic.
On the contrary, PostgreSQL requires you to define a schema before loading the data, restricting data with different formats. It provides flexibility in terms of user-defined functions and stored procedures, through which you can implement custom logic on your data to enhance data modeling.
Cost
Being a fully managed service, Amazon DynamoDB offers a pay-as-you-go pricing model, providing you the flexibility to select features according to your requirements and budget. The overall associated costs depend on multiple factors, including the amount of data stored, read and write capacity, and features like backup and restore.
In hindsight, PostgreSQL is an open-source tool that is free to use and can easily be installed on any system. However, factors like hardware resources define the total cost of maintaining and managing a database.
When comparing DynamoDB vs Postgres cost, the key difference is that DynamoDB has a defined price but provides infrastructure management. While Postgres is a free to use tool, it can require extensive hardware and expertise in database management.
Use Cases
DynamoDB is an effective tool for applications that interact with semi-structured and unstructured data. It is a highly scalable database management system with use cases spread across multiple domains. Some of the common use cases of DynamoDB are game development, real-time analytics, and IoT applications.
PostgreSQL, on the other hand, is a robust relational database management system that deals with structured data. Some applications where it is prominently used are content management systems, banking, data warehousing, and e-commerce.
Streamline Data Movement to DynamoDB or PostgreSQL with Airbyte
Consolidating your data into DynamoDB or PostgreSQL is essential to enhance data management and accessibility. However, manually replicating data into these platforms can be complex and time-consuming. To streamline data migration, you can use no-code tools like Airbyte.
Airbyte is a data integration platform that enables you to migrate data between different systems, including DynamoDB and PostgreSQL. It offers a library of 400+ pre-built connectors, which you can use to replicate structured, semi-structured, and unstructured data into a centralized repository. If the connector you seek is unavailable, you can leverage Airbyte’s Connector Development Kit (CDK) to build custom connectors.
Here are a few key features of Airbyte:
- Developer-Friendly Pipelines: PyAirbyte is an open-source library for building data pipelines using Python. With this feature, you can extract data from multiple sources using Airbyte connectors and load it into SQL caches to create data-intensive applications.
- Schema Management: Airbyte allows you to mention how it must handle source schema changes. After configuration, Airbyte conducts schema checks once every 15 minutes for cloud users and once every 24 hours for self-hosted users.
- Change Data Capture: Using the CDC feature, you can automate identifying changes made to the source data and replicate them to the destination. It allows you to ensure data consistency by tracking the updates.
- Advanced Security: Airbyte adheres to popular industry-specific regulations and standards, such as SOC 2, GDPR, HIPAA, and ISO 27001, to safeguard your data against unauthorized access.
- Active Community: Airbyte has an active community with over 15,000 users and 800+ developers, offering community-driven connectors, resources, and plugins.
Key Takeaways
Using this guide, you can choose the tool between DynamoDB vs PostgreSQL that best fits your requirements. If you need a robust NoSQL solution for scaling your application while managing data in different formats, DynamoDB is a better option. On the other hand, if your application requires management of structured data, PostgreSQL is a good tool.
Once you select the database, you can consolidate your data to enhance data accessibility. To simplify the data migration process, you can leverage Airbyte. With its user-friendly interface, Airbyte reduces the time spent integrating platforms, even facilitating data migration from DynamoDB to PostgreSQL.