We live in a world today where we have too many choices. Having too many choices creates a lot more work if we aren't sure what we want or what we are looking for. Here's a quick high-level run down of 10 familiar proprietary database systems.

Database System Types

1. Relational Databases

   • Attributes & Properties:

     • Strict adherence to table and column design.

     • Utilizes SQL (Structured Query Language) for querying and managing data.

     • Database design types (schema designs) - OLTP, RDBMS, Star Schema, Snowflake Schema.

   • Use Cases:

     • General-purpose data storage and retrieval for structured data. Small or Large scale.

1. SQL Server

   • Microsoft's relational database management system (RDBMS) using SQL.

   • Widely used in enterprise-level applications and businesses.

2. MySQL

   • Open-source relational database management system (RDBMS) using SQL.

   • Known for its speed, reliability, and ease of use.

3. Oracle

   • A powerful and widely used commercial RDBMS using SQL.

   • Commonly used in large enterprises and critical applications.

4. Snowflake

   1. According to ChatGPT

      • A cloud-based data warehousing platform.

      • Designed for handling and analyzing large volumes of data.

   2. I would add that Snowflake is also excellent for small volumes of data as well.

5. Postgres (PostgreSQL)

   • Open-source, object-relational RDBMS using SQL.

   • Known for its extensibility and support for various data types.

1. Document / NoSQL

   1. MongoDB

      • A popular NoSQL database using a document-style data model.

      • Utilizes MQL (MongoDB Query Language) for querying.

   2. DynamoDB

      • A managed NoSQL database service by Amazon Web Services (AWS).

      • Designed for high performance and scalability, utilizing a key-value and document data model.

   3. Apache Cassandra

      1. Open Source

2. OLAP (Online Analytical Processing) Databases

   • Attributes & Properties:

     • Specialized for aggregating and analyzing large volumes of data.

   • Use Cases:

     • Business intelligence, data analysis, and decision support systems.

1. Language - MDX (Multidimensional Expressions)

   • A query language used in OLAP databases for multidimensional analysis.

1. Hadoop / Big Data

   • Attributes & Properties:

     • Multi-server, multi-processor distributed architecture.

     • Processes massive amounts of unstructured data in parallel.

   • Use Cases:

     • Analyzing and processing large volumes of unstructured and semi-structured data.

These database types cater to a variety of data storage and processing needs, ranging from structured data in relational databases to unstructured big data in Hadoop environments. Each type has its own strengths and is suited to specific use cases based on the nature and scale of data being handled.

There are many others for those who want to dig even deeper into this subject.

https://www.gartner.com/reviews/market/cloud-database-management-systems

Please send me a note if you have a question. I would love to hear from you.