iODBC is a cross-platform Driver Manager that comforms to the Microsoft ODBC 2.x & 3.x and X/Open SQL CLI data access specs. It enables the development of database-centric solutions that are both database and platform independent. This is a great SDK for porting WIN32-based ODBC applications to Linux and other OS platforms.
SQLObject is an object-relational mapper, i.e., a library that will wrap your database tables in Python classes and your rows in Python instances. It currently supports MySQL through the 'MySQLdb' package, PostgreSQL through the 'psycopg' package, SQLite, Firebird, MaxDB (SAP DB), MS SQL, and Sybase. It should support Python versions back to 2.4.
SchemaCrawler is a Java API which makes working with database metadata as easy as working with ordinary Java objects. It is also a database schema discovery and comprehension and schema documentation tool. You can search for database schema objects using regular expressions, output the schema and data in a readable text format, and find potential design issues with lint . The output is designed to be diff-ed against other database schemas. SchemaCrawler supports almost any database which has a JDBC driver, but for convenience is bundled with drivers for some commonly-used RDBMS systems. SchemaCrawler works with any operating system which supports Java.
Groonga is a fast and accurate full text search engine based on an inverted index. Newly registered document instantly appears in search results, and updates are allowed without read locks. These characteristics result in superior performance for real-time applications. It is also a column-oriented database management system (DBMS). Compared with well-known row-oriented systems, such as MySQL and PostgreSQL, column-oriented systems are more suited for aggregate queries.
DataCleaner is a data quality analysis tool that allows you to perform data profiling, validating, and minor ETL-like tasks. These activities help you administer and monitor your data quality in order to ensure that your data is useful and applicable to your business situation. It can be used for master data management (MDM) methodologies, data warehousing projects, statistical research, preparation for extract-transform-load activities, and more.