Challenges of NoSQL

A NoSQL originally referring to non SQL or non relational is a database that provides a mechanism for storage and retrieval of data. This data is modeled in means other than the tabular relations used in relational databases. For a variety of reasons, businesses rely on relational database technology that has been around for decades. Long-running, mission-critical applications are frequently supported by relational databases, which have robust technology and expert support. However, as new Big Data use cases and applications develop, businesses are turning to NoSQL database technology to meet their needs.

In comparison to traditional relational databases, NoSQL databasesprovide a more flexible data model, horizontal scalability, and greater performance. However, these advantages come with certain NoSQL database problems.

Challenges of NoSQL:

• Back-ups in Application Consistent: Determining the sequence of changes across replicas, which is critical in selecting which values should compose a snapshot, is a typical difficulty in quorum-based replication systems. For example, determining a rigorous ordering between two write requests to the same database object that arrived at two distinct nodes at the same time is challenging. As a result of the absence of ordering, determining the most recent value of a database item at any given time is difficult.
• Maturity: NoSQL proponents would agree that increasing demands will inevitably lead to obsolescence, but the RDBMS maturity cycle appears to be more secure. RDBMS is more reliable and functional since it has been around for decades. Many NoSQL alternatives are still in the pre-production stage and do not yet have all of their essential features implemented.
• Database and node failures during backups and restores : Node failures are common in NoSQL databases since they are designed to grow to hundreds of nodes. As a result, any backup method must be able to account for data collection failures from down nodes and their influence on quorum consistency. On the other hand, restorations must take into consideration failed cluster nodes and modify data re population correspondingly.
• Analytics and business intelligence: NoSQL was created to fulfill the needs of Web 2.0 applications, and as a result, all of its characteristics are geared toward that goal. Other commercial systems, on the other hand, necessitate moving beyond the insert-read-update-delete cycle. Even the most basic queries need extensive programming knowledge, and integrated BI tools are insufficient.
• Performance :  Consider the same system as before in terms of performance (RPOs and RTOs). Because it is impossible to parallelize database file processing beyond a certain point, it will be impossible to achieve customer SLAs in terms of RTO if per row processing is sluggish. Due to the same parallelization limitations, recovery procedures are also impacted. This means that backup and recovery processing for 100 billion rows over 10 million files must be quick, and a solution must dramatically minimize per-row and per-file database file processing.
• Data Integrity: Verifying data integrity at the block level is another issue with distributed NoSQL databases. Checksum work for scale-up databases because the restored data is physically identical to the backup data. The restored data in scale-out databases is semantically comparable to the backup data, but it is not physically identical. In this situation, we’ll need to come up with a unique method for identifying semantic equivalence between recovered and backup data, which will allow us to spot data corruption issues that may arise throughout the backup and restoration process.
• Expertise: Despite the fact that there are millions of developers throughout the world, the majority of them are familiar with RDBMS architecture. All NoSQL developers should be considered to be in the early stages of their careers and have yet to achieve expert status. While this problem will eventually be resolved, selecting the correct developer is now difficult.
• De-duplication: In traditional database systems, de-duplication is simple—a block with identical bitwise values. Data copies are not always identical in modern NoSQL database storage systems because the sequencing and flushing of changes vary between nodes, creating a new challenge for de-duplication.

Because of their increased capabilities/capacity and economies, NoSQL databases are becoming more popular. However, developers should exercise caution and be mindful of the system’s real limits.