Introduction of NewSQL | Set 2
- The term NewSQL is not exactly as wide as NoSQL. NewSQL systems all begin with the relational data model and the SQL query language and they all attempt to cover portion of similar types of scalability, flexibility or lack-of-focus that has driven the NoSQL development. Many offer more grounded consistency guarantees.
- However, inside this group there are numerous distinctions. HANA was made to be a business reporting system which could handle a transactional load a perfect fit for deployment of SAP. In traditional Microsoft SQL server in-memory processing ability is added by Hekaton. Both the systems are designed in order to improve the OldSQL systems directly.
- NuoDB is first cluster based SQL database, which runs on multiple nodes over various datacenters and make underlying system manage data consistency and locality for you This comes at a cost in performance and consistency for arbitrary workloads. NuoDB is the closest to being called eventually consistent of the NewSQL systems.
- MemSQL focus on the clustered analytics, MemSQL provide faster analysis of OLAP as compared to Old SQL systems.
- VoltDB is most stable database system among these systems, which combines analysis of streaming data, native clustering and strong ACID guarantees. This permit VoltDB to be the system of record for the applications which are data intensive, while providing combine high throughput, low latency ingestion engine.
- Possibly you have huge amount of data which require high speed transactional access You have incoming data stream and require transactions to calculate responses and analysis in real time. The data analysis and decision making must be computed me request in batch processing scenario. In such case NewSQL systems become useful.
The NewSQL Advantages
- Less complex applications, greater consistency.
- Convenient standard tooling.
- SQL influenced extensions.
- More traditional data and query models for NoSQL-style clustering.
The NewSQL Disadvantages
- Less generalized as current SQL.
- For terabytes, memory architectures are inefficient.
- Access to the rich tooling of current SQL systems is rational.
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