SQL is a standard language used by developers, DBAs, and business analysts to query data sets. Traditional SQL databases offer rich transaction capabilities, ad-hoc query and reporting capability, and vast amounts of standards-based tooling. Where they fall short is in the ability to scale out to meet the needs of modern, high-performance applications.
NoSQL was a solution to issues of scale that emerged as organizations began dealing with immense volumes, velocity, and variety of big data from a multitude of sources. NoSQL solutions offered availability, flexibility and scale. However, they came with difficult tradeoffs - sacrifice of data consistency and transactional (ACID) guarantees, loss of ad-hoc query capability and increased application complexity. Trading off data consistency and ACID in many cases means application developers, who are not distributed data infrastructure experts, have had to try and fill the gap. Now that you’ve got an overview of SQL vs NoSQL, who do you need to help you build and maintain your database systems? Relational and non-relational database management systems can get extremely complicated, and definitely require upkeep—especially when you factor in moving to the cloud. While it’s easy to manage a basic single-file database in a program you’ll want to hire a capable database architect to handle your relational database management system (RDBMS) or NoSQL database management.In 2016, we partnered with Research Now to conduct a survey on a subject we take very seriously: data consistency. The results were shocking. While there was wide agreement on what is defined by “critical data” (financial data), only 58% of people surveyed stated that...
We looked at the basic differences between NoSQL and NewSQL in a recent post. Now let’s break the differences down specifically by looking at what developers really care about: Which problems can I solve with NoSQL? Equally important, where is NoSQL a bad fit? Where...
NoSQL and NewSQL databases are popular solutions in the data management space. We’re sometimes asked to clarify the difference between the two approaches. Here’s what you need to know if you’re trying to decide which solution to adopt in your organization. NoSQL vs. NewSQL: What's the...
A recent blog post described SQLCoverage, a VoltDB-developed Python tool that tests VoltDB by running millions of queries using randomized data and comparing the results with the those of identical queries run against HSQLDB, an open-source relational database. This blog post continues that discussion by...
A previous blog post by Ruth Morgenstein, VoltDB Director of QA, gave an overview of how we test at VoltDB. Read that for brief descriptions of our robust processes and culture of quality, including Agile development, continuous integration using Jenkins, Java and C++ unit tests, system integration tests, performance tests, and related topics.
Trying to choose a database to solve a problem (or a whole set of them)? Here's a quick rundown of the advantages - and disadvantages - of NoSQL versus NewSQL. Choosing the right tool for the job at hand is 80 percent of getting to...
The sale and subsequent closure of FoundationDB cut short something of a grand experiment. FoundationDB, conceived as a Key-Value store, had decided to add flexibility in the form of programming and query-model “Layers” on top of its core KV store. First up was SQL, software...