More and more application developers choose NoSQL databases as operational databases. They choose technologies like Apache HBase, Apache Phoenix and MongoDB because of their scalability, schema-less flexibility, and fast response time for short-request queries.
As NoSQL databases store more application data, enterprises want to perform analysis on that data. But while NoSQL data stores are well-suited to operational queries, most NoSQL databases are not optimized for analytic queries. For example, a key-value store is extremely fast when looking up information given a key--such as a user profile. But it is 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.
Nonetheless, Zoomdata can provide visual analytics for data stored in NoSQL stores. And, Zoomdata is smart enough to push down whatever query processing can be done to the NoSQL source such as aggregations in MongoDB. If the source doesn’t natively support analytic queries, Zoomdata leverages Apache Spark to supplement the capabilities of the NoSQL source.
Zoomdata 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 Zoomdata.
Zoomdata provides visual analytics for data in NoSQL stores including MongoDB, Apache Phoenix, and Apache HBase.