The SlamData BI Connector: MongoDB to Microsoft Power BI
The SlamData BI Connector is provided as an open source alternative to MongoDB’s BI Connector which is part of the paid edition of MongoDB. Both of these connectors are primarily for companies that already use and have large investments in existing BI tools. SlamData BI Connector is based on the Quasar NoSQL analytics engine and offers superior performance and analytics compared to the MongoDB BI Connector.
Connect and Go!
It’s not easy to connect today’s BI (Business Intelligence) tools to NoSQL Data. Complicated ETL processes or expensive ODBC drivers are required, until now! Zero setup, just install and let the SlamData BIC do the heavy lifting with any BI or Visual analytics tool.
Retain the Value of Your BI Investments
Companies have spent big money on legacy BI (Business Intelligence) tools and training and are rightfully disappointed to find they cannot use them with their NoSQL data. With SlamData BIC you can empower with access to modern NoSQL data without needing to learn new tools, the best of both worlds.
Native Access to MongoDB Data
BI connectors can be useful tools, but when dealing with complex NoSQL data they have several well documented limitations . If you need fast, flexible and native analytics for NoSQL and JSON data check out SlamData Advanced Edition.
- 100% Native analytics on JSON data
- Full support of nested data and arrays
- Explore, Search and Query your NoSQL Data with ease
The Characteristics of NoSQL Analytics Systems
This paper carves out a single concern, by focusing on the system-level capabilities required to derive maximum analytic value from a generalized model of NoSQL data. This approach leads to eight well-defined, objective characteristics, which collectively form a precise capabilities-based definition of a NoSQL analytics system.
- The Nature of NoSQL Data
- NoSQL Databases
- Big Data
- A Generic Data Model for NoSQL
- Approaches to NoSQL Analytics
- Coding & ETL
- Real-Time Analytics
- Relational Model Virtualization
- First-Class NoSQL Analytics
- Characteristics of NoSQL Analytics Systems
- Generic Data Model
- Isomorphic Data Model
- Unified Schema/Data
- Polymorphic Queries
- Dynamic Type Discovery & Conversion
- Structural Patterns