Amazon ElastiCache vs. Apache Ignite vs. Azure SQL Database vs. django-mysql Comparison Chart

Use Ignite as a traditional SQL database by leveraging JDBC drivers, ODBC drivers, or the native SQL APIs that are available for Java, C#, C++, Python, and other programming languages. Seamlessly join, group, aggregate, and order your distributed in-memory and on-disk data. Accelerate your existing applications by 100x using Ignite as an in-memory cache or in-memory data grid that is deployed over one or more external databases. Think of a cache that you can query with SQL, transact, and compute on. Build modern applications that support transactional and analytical workloads by using Ignite as a database that scales beyond the available memory capacity. Ignite allocates memory for your hot data and goes to disk whenever applications query cold records. Execute kilobyte-size custom code over petabytes of data. Turn your Ignite database into a distributed supercomputer for low-latency calculations, complex analytics, and machine learning.

Django-MySQL extends Django’s built-in MySQL and MariaDB support their specific features not available on other databases. A new cache backend that makes use of MySQL’s upsert statement and does compression. Named locks for easy locking of e.g. external resources. Extra checks added to Django’s check framework to ensure your Django and MySQL configurations are optimal. Django-MySQL comes with a number of extensions to QuerySet that can be installed in a number of ways - e.g. adding the QuerySetMixin to your existing QuerySet subclass.