- 13.1. Disparate Data Storage Needs
- 13.2. Polyglot Data Store Usage
- 13.3. Service Usage over Direct Data Store Usage
- 13.4. Expanding for Better Functionality
- 13.5. Choosing the Right Technology
- 13.6. Enterprise Concerns with Polyglot Persistence
- 13.7. Deployment Complexity
- 13.8. Key Points
This chapter is from the book
This chapter is from the book
This chapter is from the book
13.6. Enterprise Concerns with Polyglot Persistence
Introduction of NoSQL data storage technologies will force the enterprise DBAs to think about how to use the new storage. The enterprise is used to having uniform RDBMS environments; whatever is the database an enterprise starts using first, chances are that over the years all its applications will be built around the same database. In this new world of polyglot persistence, the DBA groups will have to become more poly-skilled—to learn how some of these NoSQL technologies work, how to monitor these systems, back them up, and take data out of and put into these systems.
Once the enterprise decides to use any NoSQL technology, issues such as licensing, support, tools, upgrades, drivers, auditing, and security come up. Many NoSQL technologies are open-source and have an active community of supporters; also, there are companies that provide commercial support. There is not a rich ecosystem of tools, but the tool vendors and the open-source community are catching up, releasing tools such as MongoDB Monitoring Service [Monitoring], Datastax Ops Center [OpsCenter], or Rekon browser for Riak [Rekon].
One other area that enterprises are concerned about is security of the data—the ability to create users and assign privileges to see or not see data at the database level. Most of the NoSQL databases do not have very robust security features, but that’s because they are designed to operate differently. In traditional RDBMS, data was served by the database and we could get to the database using any query tools. With the NoSQL databases, there are query tools as well but the idea is for the application to own the data and serve it using services. With this approach, the responsibility for the security lies with the application. Having said that, there are NoSQL technologies that introduce security features.
Enterprises often have data warehouse systems, BI, and analytics systems that may need data from the polyglot data sources. Enterprises will have to ensure that the ETL tools or any other mechanism they are using to move data from source systems to the data warehouse can read data from the NoSQL data store. The ETL tool vendors are coming out with have the ability to talk to NoSQL databases; for example, Pentaho [Pentaho] can talk to MongoDB and Cassandra.
Every enterprise runs analytics of some sort. As the sheer volume of data that needs to be captured increases, enterprises are struggling to scale their RDBMS systems to write all this data to the databases. A huge number of writes and the need to scale for writes are a great use case for NoSQL databases that allow you to write large volumes of data.