Open Source Database

Open Source Database Definition

An open source database has code that is open and free for download, modification and re-use. This is the opposite of a proprietary or closed source database in which the code is protected to prevent copying.

Open Source Database diagram showing readable code syncing between databases.


What Are Open Source Databases?

Open source databases store vital information in software which the organization can control. An open source database allows users to create a system based on their unique requirements and business needs. It is free and can also be shared. The source code can be modified to match any user preference.

Open source databases address the need to analyze data from a growing number of new applications at lower cost. The deluge of social media and the Internet of Things (IoT) has ushered an age of massive data that needs to be collected and analyzed. The data only has value if an enterprise can analyze it to find useful patterns or real-time insights. But the data contains vast amounts of information that can overload a traditional database. The flexibility and cost-effectiveness of open source database software has revolutionized database management systems.

The most common open source databases include:

  • Key-value databases — Store key and value data in memory for speedy lookup.
  • Document databases — Store document information.
  • Wide-column store databases — Similar to key-value with a large number of columns. They are well suited for analyzing huge data sets.

Graph databases — Explore the relationships that link data together, allowing rapid execution of complex queries over millions of connections. Use cases include recommendations, social networks and fraud detection.

How Is An Open Source Database Used In Analytics?

An open source database is used in analytics to review vast amounts of data so enterprises can better determine business goals. Open source data software is now common in enterprise IT departments in many industries. The best open source database examples include companies such as:

  • Macy’s — Using open source data technology to reach customers with advertising campaigns targeted to their specific tastes and needs.

  • Progressive Insurance — Analyzing more than 15 billion miles of driving data with its Snapshot program to give safer drivers discounts.  

Netflix — Runs its own Open Source Software Center as a user and contributor to open source databases for knowing which content customers will prefer.

Closed Source Versus Open Source Database

Closed source databases have private source code that cannot be accessed or modified. The code cannot be checked for bugs or corrected by anyone outside the company that made the code. Updates or patches can take a long time to complete. Closed source software and databases also have costly licenses that require renewal.

Open source databases are free and open for anyone to use. The source code can be downloaded and modified. A user can tailor the code to their own needs and distribute it freely without vendor lock-in.

What Is Spatial-temporal Reasoning?

Spatial-temporal reasoning is what a person or a robot with artificial intelligence uses to understand how items fit together in a space. It is accomplished by picturing a spatial pattern. This includes visualizing a step-by-step process and how objects can be manipulated into different patterns.

Spatial–temporal reasoning is key for problem-solving and organizational skills. It is used in computer science to help robots understand and navigate time and space. Spatial-temporal reasoning is also used in cognitive psychology to explore how a mind processes its knowledge of time and space.

What Is An Open Source Database Management System?

Open source database management systems reduce the costs associated with the licences of traditional closed database systems. Organizations can also experience greater efficiency by tailoring the database system to meet their specific needs.

The first open source database management system was MySQL in 1995. Since then, there have been many improvements and additional features in open source database management that make it preferred by many enterprises today.

Does HEAVY.AI Offer An Open Source Database?

Yes. HEAVY.IDB and associated visualization libraries are available on Github under an Apache 2.0 license. It provides everything required to build a fully functional installation of HEAVY.AiDB, enabling sub-second querying across many billions of records on a multi-GPU server.

HEAVY.AI pioneered the use of graphics processing units (GPUs) to analyze multi-billion-row datasets in milliseconds, orders-of-magnitude faster than traditional CPU-based systems. By offering an open source GPU database, HEAVY.AI is making the world’s fastest analytics platform available to everyone.