Many enterprise application developers choose NoSQL databases as operational databases. They employ technologies like Apache HBase, MongoDB, Cassandra and Presto for their scalability, schema-less flexibility, high write speed, and fast response time for short-request queries. These are its advantages over relational, SQL-based data models.
As NoSQL databases store more application data, enterprises want to perform analytics on that data. But while NoSQL big data stores are well-suited to operational queries, most NoSQL databases are not optimized for analytic queries or business intelligence. For example, a key-value store is extremely fast when looking up information given a key such as a user profile or a key-value pair. But it’s much more challenging to select a subset from millions of profiles based on arbitrary filters or to aggregate across millions of records. In fact, some NoSQL stores don’t support aggregation or ad hoc filtering on an arbitrary field.
NoSQL Business Intelligence
Traditional BI tools provide either very basic or no support for NoSQL databases. In cases where they are supported, connectors tend to be via non-native JDBC or ODBC drivers. Performance is very slow due to the data management overhead imposed by the non-native connectors, and the fact that NoSQL database engines aren’t capable of the query operations demanded for BI and analytics.such as group-by summaries of big data.
Logi Composer Native Smart Connectors For NoSQL Databases
Logi Composer can provide visual analytics for business users with data stored in NoSQL databases. And, Logi Composer is smart enough to push down whatever query processing can be done to the NoSQL source, such as aggregations in MongoDB. In fact, MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function, and single-purpose aggregation methods.
If the source doesn’t natively support analytic queries, Logi Composer leverages Apache Spark to supplement the capabilities of the NoSQL source. Logi Composer also supports NoSQL characteristics that are different from relational sources, such as nested structures. So if you’ve got valuable data in NoSQL stores, you can tap into that value with visual analytics from Logi Composer.