Accuracy and consistency for big data processing and reporting.

It used to be that if you required accuracy and consistency with your data you stored it in a traditional relational database.  Thus RDBMS systems still form the backbone of day-to-day operational processes and reporting across many industries.  In today’s high-speed, 24/7, tightly monitored world, the incapacity of RDBMS to handle large volumes of data is becoming increasingly problematic.

In contrast, the more recent development of ‘big data’ technologies have provided powerful insights, approximations, trends, market intelligence on vast quantities of data, but lack the absolute accuracy and consistency of RDBMSs. Both technologies offer significant benefits and limitations.  

A relational database achieves its guarantees of accuracy and consistency through the use of transactions. A transaction ensures that a set of changes either all happen or all do not. Without such a mechanism to make these guarantees, a changing data set is likely to become inconsistent and subsequent processes that rely on that data will be inaccurate.

The Cyoda platform combines the power of both transactional consistency and big data scalability. Transactions are distributed so there are no bottlenecks to restrict the volume or complexity of data queries. The platform also incorporates a scalable rules engine which can be configured to apply virtually any business process – so there are no limits either to the amount of data or complexity of processing that can be modelled.

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Further reading:


STP Processing

Easy Integration

Distributed Queries

Scale Without Limits

Technical Overview