Postgres vs MarkLogic

Built by passionate developers, available for free, and is well supported by its active community.

With the extensive SQL support and migration tools, Postgres users are easily able to migrate their databases over to the Postgres database with little effort.

JSON support allows for Postgres to transfer data as raw text and without attributes and markup overhead. This will result in new levels of speed, efficiency and flexibility for developers.

Continues to work well under low or heavy loads in order to meet the users' need.

You can reuse existing approved design table and extend its capability by inheritance. You can reuse ancestor method byy declaring new trigger for descendant but reuse ancestor trigger procedure. You can add, remove or override column constraint making it differ from its ancestor. Applying OOP with database design help me reuse, extend, and encapsulate business logic and end up a rapid design, and less errants. PostgreSQL is a powerful RDBMS while its OOP is sufficient for OOP modular design. Especially its Open Source ,and free.

Built in, so users won't have to worry about atomicity, consistency, isolation and the durability of the database.

Postgres uses MVCC. For each user connected to the database the Postgres database shows a snapshot of the database at a particular instance. When the database needs to update an item it will add the newer version and mark the old version as obsolete. This allows the database to save overhead but requires a regulated sweep to delete the old, obsolete data.

"There are interfaces for Java (JDBC), ODBC, Perl, Python, Ruby, C, C++, PHP, Lisp, Scheme, and Qt just to name a few."

Unlike MySQL, you generally don't spend time on hinting the query planner in order to make PostGres perform well.

For example:

INSERT INTO table (field_1, field_2, field_3) VALUES (value_1, value_2, value_3) RETURNING id;

No other ACID database has even close to the text handling capabilities that are built-in to MarkLogic. Many multi-model databases rely on Lucene to provide text indexing, which leads to unnecessary latency and complexity.

Configuring MarkLogic for scale out is simple with both APIs and UI based mechanisms to add and manage cluster nodes that auto-shard and redistribute themselves for maximum efficiency.

MarkLogic supports XML natively and adheres to all W3C standards surrounding XML. It even uses XQuery as a powerful application engine. Recent editions are also JSON native, which makes it fit in with modern JavaScript and web-centric applications.

MarkLogic is the only Multi-model database in the world that is fully ACID and treats unstructured content as a first class citizen.