Companies have had to rely on highly skilled users to get the most from their graph-based data - until now, that is. With the new Neo4j BI Connector, advanced analytics and graph data are now accessible to a broad spectrum of Business Intelligence tool users, regardless of Neo4j or Cypher expertise.
When Neo4j Inc. introduced the world’s first native graph database over 10 years ago, the Company established a new category of enterprise software that can store, query, analyze and manage highly connected data more efficiently than other database types. Today, Neo4j is the leading graph database, helping over 300 enterprise customers and more than 75% of the Fortune 100 with connected data applications.
The Growing Popularity of Graph Data
Graph databases are growing increasingly important, especially among businesses and data scientists, as new classes of big data analytics and transaction challenges emerge. Unlike traditional database software that stores information in tables, a graph database stores information as a network of nodes and relationships. Each node represents an entity (a person, thing, place, category or other piece of data), and each relationship represents how two nodes are associated. This structure allows users to generate new and powerful insights from the relationships in large collections of data. The Neo4j platform, for example, is used in applications ranging from recommendation engines and fraud detection to social networking and beyond.
Graph databases are finding a place in analytics applications across industries:
As more and more companies adopted Neo4j into their enterprise environments, the Company noticed a gap between Neo4j power users and traditional business analysts. These analysts wanted to realize the value of Neo4j, but lacked the skills in graph-specific data visualization tools or in Neo4j’s powerful Cypher query language. Analysts, by and large, are more familiar with tools such as Tableau, MicroStrategy, and Looker as well as other well-known business intelligence applications.
BI tools require specialized connectors, also called JDBC or ODBC drivers, to communicate with various data sources. Up until recently, Neo4j had no such connector for BI tools that was SQL capable. That’s where the Neo4j and Simba partnership comes in.
Simba, the leader in ODBC/JDBC connectivity, working with Neo4j, developed a new JDBC driver to fill this functionality void. The two companies recently released a jointly developed JDBC-based driver, the Neo4j BI connector, that simplifies BI tool access to Neo4j data in the enterprise. More importantly, it enables business users who are less familiar with Neo4j and Cypher to easily connect to Neo4j in applications like Tableau and MicroStrategy. The Neo4j BI connector is the first enterprise-ready driver to seamlessly integrate with the most popular BI platforms.
The Neo4j BI Connector provides access to Neo4j graph data throughout the organization by enabling analysts, knowledge workers, and data scientists to take advantage of graph data with the BI tools they are familiar with. It reduces the need for Neo4j power users and custom ETL jobs and eliminates the need for scripting and code. BI users can analyze graph data alongside traditional data stored in relational and NoSQL databases, in real time, with skills they’ve already mastered. It ensures users that all of their other data sources will be in sync with Neo4j.
Because the BI Connector is a JDBC driver, it allows the BI applications to talk to the database in a general way. The driver takes aSQL query input from the BI tool and translates it into a Cypher query. The Cypher query is executed against the database via a standard Bolt connection, and the results are sent back to the client. The BI Connector looks like any other standard Cypher / Bolt client to Neo4j.
A BI application, in general, connects to a database and gets a list of relational tables that the database provides. Then the application issues any SQL queries that it might need to run, and uses that data as needed. Most BI tools look at data through a relational lens, but in Neo4j there are no tables, only nodes and relationships in a graph. The Neo4j BI Connector gets around this by looking at the graph schema in Neo4j, building a virtual relational schema, and exposing one table per unique node label combination, and one table per relationship pair found in the graph.
Neo4j and Simba are excited about the initial release of the BI Connector and the benefits it provides. We continue to improve the driver both with performance enhancements and new functionality. The technical teams are focused on:
- Expanding Data Types for SQL equivalents
- Reducing data over-fetching
- Custom Cypher power user feature
In a few short months, the Neo4j/Simba partnership produced the first enterprise-ready driver to provide real-time, connected data results to BI users in a seamless manner. Simba has a history of providing best-in-class off-the-shelf and custom OBDC/JDBC drivers and for all kinds of data sources. We partner with our customers to help them go to market more quickly and more cost-effectively, enabling end users to access and analyze data across a multitude of applications sources so that they make better business decisions.
Discover how to add data connectivity to your custom business intelligence or data integration applications, or contact our Sales Team directly.