After data is processed, it is loaded into target database. This target database could be a relational database, a big data database or a data warehouse appliance.
Relational database could be used for a set amount of data, but with increasing data, it has its own challenges and limitations.
Apart from relational database, big data databases like Hadoop, Druid, Cassandra, Hive, Impala, etc., can also be used for building a data warehouse.
There are specialized data warehouse appliances which are columnar in nature, allowing very high speeds during read operations. Example: Ingress, Vertica, Hana, MemSQL, DB2, etc.
There are also cloud-based DW which could be used such as Amazon Redshift, dashDB, Google Query, Azure SQL, etc.
Different kinds of databases and data storage come with their own share of advantages. With concept of polyglot persistence gaining traction, it is now possible to use multiple databases for powering a single application. This helps leveraging the advantage of each database.
We, at Helical, have rich experience in data modelling and data warehousing, and have hands-on experience with various kinds of databases. We can work with you and based upon your data size and performance requirement, we can provide consulting as well as build the data warehouse solution for you.