Database application development is the process of obtaining real-world requirements, analyzing requirements, designing the data and functions of the system, and then implementing the operations in the system. It is then followed by iterative cycles of maintenance and improvements due to changing requirements and evolving data.
Our database development service is available for the development and maintenance of relational (SQL) databases as well as NoSQL databases. Types of projects are provided below, many of which also require a software client for database access and/or editing:
- Data integration from multiple, non-compatible, data sources into one searchable database system
- Database for web application systems
- Project management system
- Sample tracker database
The types of databases we are available to help with include:
- Relational databases store data ss a collection of data items with pre-defined relationships between them. These items are organized as a set of tables with columns and rows. Tables are used to hold information about the objects to be represented in the database. PostgreSQL, MySQL and Oracle Database are popular relational databases.
- Document databases store data in documents similar to JSON (JavaScript Object Notation) objects. Each document contains pairs of fields and values. The values can typically be a variety of types including things like strings, numbers, booleans, arrays, or objects, and their structures typically align with objects developers are working with in code. Because of their variety of field value types and powerful query languages, document databases are great for a wide variety of use cases and can be used as a general purpose database. They can horizontally scale-out to accomodate large data volumes. MongoDB is consistently ranked as the world’s most popular NoSQL database.
- Key-value databases are a simpler type of database where each item contains keys and values. A value can typically only be retrieved by referencing its value, so learning how to query for a specific key-value pair is typically simple. Key-value databases are great for use cases where you need to store large amounts of data but you don’t need to perform complex queries to retrieve it. Common use cases include storing user preferences or caching. Redis and DynanoDB are popular key-value databases.
- Wide-column stores store data in tables, rows, and dynamic columns. Wide-column stores provide a lot of flexibility over relational databases because each row is not required to have the same columns. Many consider wide-column stores to be two-dimensional key-value databases. Wide-column stores are great for when you need to store large amounts of data and you can predict what your query patterns will be. Wide-column stores are commonly used for storing Internet of Things data and user profile data. Cassandra and HBase are two of the most popular wide-column stores.
- Graph databases store data in nodes and edges. Nodes typically store information about people, places, and things while edges store information about the relationships between the nodes. Graph databases excel in use cases where you need to traverse relationships to look for patterns such as social networks, fraud detection, and recommendation engines. Neo4j and JanusGraph are examples of graph databases.