Databases are fundamental for training all kinds of machine learning and artificial intelligence (AI) models. Over the last two decades there has been an explosion of datasets available on the market, making it much more difficult to choose the right one for your tasks. At the same time, the larger number of data sets means you can find the perfect fit for your intended application.

Here is a list of the top 10 databases for machine learning and AI:

1.MySQL

Powered by Oracle, MySQL is one of the most popular databases on the market. Created in 1995, it has always been one of the best open source relational database management systems (RDBMS) used by big companies like Facebook, Twitter, Uber and Youtube.

What led to its rise in popularity? For one, MySQL offers enterprise-grade gestures and a free, flexible community license. It also has an enhanced commercial license and emphasizes robustness and stability.

Here are some of the main advantages of MySQL:

• Layers of data security to protect sensitive data.
• Scalability when there are large amounts of data.
• Open source RDBMS with two distinct licensing models.
• Multi-master ACID transactions through MySQL Cluster.
• Supports both structured data (SQL) and semi-structured data (JSON).

2. Apache Cassandra

Another prominent machine learning and AI database is Apache Cassandra, which is an open source and highly scalable NoSQL database management system. Apache Cassandra was designed with the goal of processing massive amounts of data extremely quickly. The database is also used by big names like Instagram, Netflix, and Reddit.

Here are some of the main benefits of Apache Cassandra:

• Handles massive volumes of data.
• One of the most scalable databases with automatic partitioning.
• Provides linear horizontal scaling.
• Decentralized database with multi-datacenter replication and automatic replication.
• Fault tolerance by automatically replicating data across multiple nodes.

3. PostgreSQL

PostgreSQL is one of the best open source object relational database systems. It extends the SQL language and combines it with various features to scale and securely store highly complex data workloads. PostgreSQL is especially useful for developers looking to build applications or administrators looking to protect data integrity. It also helps in creating fault-tolerant environments.

Here are some of the main benefits of PostgreSQL:

• Highly secure with a robust access control system.
• Offers the ACID transactional guarantee.
• The PostgreSQL Citus Data extension offers distributed SQL functionality.
• Advanced indexes such as Partial Index and Bloom Filters.
• Supports structured data (SQL), semi-structured data (JSON, XML), key-value and spatial data.

4. Sofa base

Couchbase is a document-driven engagement database that is also open source and distributed. The server offers excellent performance in any cloud and supports applications with its various features, such as workload isolation, memory-centric architecture, and geo-distributed deployments. It is capable of maintaining 99.999 availability and sub-millisecond latencies.

One of the main advantages of Couchbase is that the Couchbase data platform provides easy and powerful application development APIs in various programming languages, connectors and tools. This makes it easier to build apps while accelerating time to market.

Here are some of the main advantages of Couchbase:

• Includes built-in Big Data and SQL integration to allow users to take advantage of processing capacity, tools and data.
• Supports all cloud platforms.
• Memory-First architecture enables fast and consistent experiences at scale.
• Provides security across the entire stack.

5. Elastic Search

Another of the best database choices, Elasticsearch is based on Apache Lucene. It is a distributed and open-source search and analysis engine that supports all types of data, such as numeric, textual, geospatial, structured and unstructured data.

Elasticsearch belongs to the Elastic Stack, which includes various open-source tools for enrichment, data ingestion, storage, visualization, and analysis.

Here are some of the main benefits of Elasticsearch:

• Many built-in features such as data rollups and index lifecycle management for storing and searching data.
• Extremely efficient for full text search.
• Useful for infrastructure monitoring, security analysis, and other security-related tasks.
• Horizontal scaling via automatic partitioning.
• Part of the larger Elastic Stack which includes Elasticsearch, Kibana, Logstash and Beats.

6. Say it again

Redis is one of the most popular choices out there. It is an open source in-memory data structure used as a database, message broker, and cache. One of the main features of Redis that attract customers is its support for various data structures such as strings, sorted sets, bitmaps, geospatial indexes, hyperloglogs, etc. Redis also offers Lua scripting, LRU eviction, built-in replication, transactions, and various levels of disk persistence.

Here are some of the main advantages of Redis:

• Automatic failover process.
• Redis-ML, which is a module that implements various machine learning models as built-in Redis data types.
• Variety of data structures such as strings, lists, sets, hashes, bitmaps, streams, etc.
• Makes it easier to write complex code with fewer, simpler lines.

7. DynamoDB

A fully managed multi-regional database, Amazon DynamoDB offers built-in security, in-memory caching, backup, and recovery. The popularity of the database can be seen in the number of large companies using it, such as AirBnB, Toyota and Samsung. It performs encryption at rest to reduce the complexity usually needed to protect sensitive data.

Two of DynamoDB’s main advantages are its scalability and data replication capabilities. With Unlimited Virtual Storage, you can store unlimited amounts of data based on your custom needs. As for the data items, they are all stored on SSDs. Replication is managed internally across different Availability Zones in a region, but it can also be made available across multiple regions.

Here are some of the main advantages of DynamoDB:

• Scales horizontally by expanding a single table across multiple servers.
• Highly secure with customizable traffic filtering, regulatory compliance automation, comprehensive database threat detection, and more.
• A fully managed service that requires no hardware or software provisioning, software patches, distributed database clusters, or installation and configuration.

8.MLDB

The Machine Learning Database, or MLDB, is an open-source system intended to tackle big data machine learning tasks. It can be used for collecting and storing data through training machine learning models or deploying real-time prediction endpoints. MLDB is one of the easiest datasets to use because it provides a complete implementation of the SQL SELECT statement. This means that it treats datasets like tables, making them easy to learn and use for data analysts already versed in an existing relational database management system (RDBMS).

Here are some of the main advantages of MLDB:

• Uses SQL as a mechanism to query data stored in the database.
• The training, modeling and discovery process in MLDB has enormous processing power.
• Supports vertical scaling with greater efficiency.

9.Microsoft SQL Server

Microsoft SQL Server is a relational database management system (RDBMS) written in C and C++. It is especially useful for extracting insights from all data by querying relational, non-relational, structured, and unstructured data. It was the most popular midrange commercial database in Windows systems for the past 30 years, and is currently one of the leading commercial database systems.

Here are some of the main advantages of Microsoft SQL Server:

• Offers the ACID transactional guarantee.
• Supports server-side scripting through T-SQL, R, Python, Java, and .NET languages.
• Multi-model database that supports structured, semi-structured, and spatial data.

10. MongoDB

The last database on our list is MongoDB, which was released as the first document database in 2009. It was designed to specifically handle document data and has been significantly improved over the past few years. MongoDB is currently the leading document database and the leading NoSQL database on the market. It provides a solution to the challenges of saving semi-structured data in the database.

Here are some of the main advantages of MongoDB:

• Horizontal scaling via auto-sharding.
• Integrated replication via primary-secondary nodes.
• Licenses including Community Server, Enterprise Server and Atlas.
• Distributed multi-document ACID transactions with snapshot isolation.
• Full-text search engine and data lake built on MongoDB