Traditional databases are very good for transactional applications. However, they are not so good when the volume is too large or the type of query that is done by the applications does not perform properly.
To improve application performance, work with larger data volumes or create apps with specific functions, for example search engines, you need to work with NoSQL databases. Systems like Solr, Elastic, Redis, MongoDB, Cassandra, Scylla DB, HBase, Impala, Hive and others are the most used in the world to handle large volumes or work with specific applications. Always with high performance and safety.
The main NoSQL databases we can build solutions for include:
- Elastic: a Lucene-based search system associated with an ingestion (Logstash) and visualization platform (Kibana). Elastic can also be used to create applications that require document search and indexing, as well as a product recommendation.
- Solr: Lucene-based search system that is embedded in several e-commerce platforms. Can be used for complex search systems that require many features and extremely personalized relevance. Can also be used for product recommendations
- Cassandra/HBase/DynamoDB/ScyllaDB: NoSQL column family databases that can work with large volumes of information.
- Redis: NoSQL database system widely used as cache and publish-subscribe system. It has high performance and is often used by a high-performance web or mobile applications to deliver high-speed content.
- Impala: High-performance analytics platform that uses the SQL language to query data in files of any format. Ideal for integrating gigantic tables with analytical business intelligence systems.
- Hive: ETL data transformation platform that uses SQL language and converts the command into MapReduce, Tez or Spark jobs to perform large data operations on distributed systems. A high-performance NoSQL technology and the most widely used big data technology in the world.