StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Amazon QLDB vs Azure SQL Database

Amazon QLDB vs Azure SQL Database

OverviewComparisonAlternatives

Overview

Azure SQL Database
Azure SQL Database
Stacks585
Followers502
Votes13
Amazon QLDB
Amazon QLDB
Stacks5
Followers17
Votes0

Amazon QLDB vs Azure SQL Database: What are the differences?

# Key Differences Between Amazon QLDB and Azure SQL Database

Both Amazon Quantum Ledger Database (QLDB) and Azure SQL Database are popular choices for storing and managing data in the cloud. However, there are key differences between the two that cater to different use cases and requirements.

1. **Data Model**: Amazon QLDB is a fully managed ledger database that provides an immutable transaction log, making it ideal for applications requiring a complete and verifiable history of changes. Azure SQL Database, on the other hand, is a relational database service that offers traditional table-based data modeling.

2. **Consistency**: Amazon QLDB ensures immediate consistency with transactions being committed in a serializable order. In contrast, Azure SQL Database supports different levels of consistency, including strong, eventual, and eventual with bounded staleness, allowing users to choose the level that suits their requirements.

3. **Purpose**: Amazon QLDB is designed for managing immutable and verifiable transaction logs, making it a good fit for applications where data integrity and auditability are critical. Azure SQL Database, on the other hand, is designed for traditional relational database use cases such as transaction processing, analytics, and reporting.

4. **Query Language**: Amazon QLDB uses PartiQL (a SQL-compatible query language) for retrieving data from the ledger database. Azure SQL Database supports T-SQL, a dialect of SQL commonly used with Microsoft SQL Server.

5. **Pricing Model**: Amazon QLDB pricing is based on the number of read and write operations, storage capacity, and data transfer. In comparison, Azure SQL Database offers different pricing tiers based on database size, performance levels, and additional features like automatic tuning and advanced security capabilities.

6. **Integration with Ecosystem**: Amazon QLDB is tightly integrated with other AWS services like AWS Lambda, Amazon S3, and IAM for seamless data processing and management. Azure SQL Database, being a part of the Azure ecosystem, offers integration with a wide range of Azure services like Azure Functions, Azure Synapse Analytics, and Azure Active Directory for comprehensive data capabilities.

In Summary, Amazon QLDB and Azure SQL Database differ in terms of data model, consistency, purpose, query language, pricing model, and integration with the ecosystem, catering to distinct requirements of users in the cloud database realm.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

Azure SQL Database
Azure SQL Database
Amazon QLDB
Amazon QLDB

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

It is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log ‎owned by a central trusted authority. It can be used to track each and every application data change and maintains a complete and verifiable history of changes over time.

-
Immutable and Transparent; Cryptographically Verifiable; Serverless; Easy to Use; Streaming Capability
Statistics
Stacks
585
Stacks
5
Followers
502
Followers
17
Votes
13
Votes
0
Pros & Cons
Pros
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable
No community feedback yet
Integrations
No integrations available
AWS Lambda
AWS Lambda
Amazon Redshift
Amazon Redshift
Amazon Kinesis
Amazon Kinesis
Amazon Elasticsearch Service
Amazon Elasticsearch Service

What are some alternatives to Azure SQL Database, Amazon QLDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase