Apache Hive vs. Apache Phoenix vs. ThinkSQL vs. django-mysql Comparison Chart

Apache Phoenix enables OLTP and operational analytics in Hadoop for low-latency applications by combining the best of both worlds. The power of standard SQL and JDBC APIs with full ACID transaction capabilities and the flexibility of late-bound, schema-on-read capabilities from the NoSQL world by leveraging HBase as its backing store. Apache Phoenix is fully integrated with other Hadoop products such as Spark, Hive, Pig, Flume, and Map Reduce. Become the trusted data platform for OLTP and operational analytics for Hadoop through well-defined, industry-standard APIs. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds for small queries, or seconds for tens of millions of rows.

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.