Nowadays NOSQL databases are becoming more popular. Companies like Google, Facebook, and Amazon has created their own NOSQL databases based on their requirements. Different types of querying approaches are followed by different NOSQL databases, whereas traditional databases like MySQL, ORACLE, etc. follows SQL for querying. Most of the companies are shifting from traditional databases to NOSQL ...

Kieker’s monitoring output can be persistently saved into logs by utilizing relational databases or file systems. Currently, there is no support for noSQL storage. As part of our Regression Benchmarking Execution Environment (RBEE) we introduce a selfcontained system offering noSQL storage capabilities and acting as gateway between Kieker and RBEE. We show, how polyglot persistence can increase...

NoSQL databases focus on analytical processing of large scale datasets, offering increased scalability over commodity hardware. One of their strongest features is elasticity, which allows for fairly portioned premiums and high-quality performance and directly applies to the philosophy of a cloudbased platform. Yet, the process of adaptive expansion and contraction of resources usually involves ...

Big Data has recently gained popularity and has strongly questioned relational databases as universal storage systems, especially in the presence of analytical workloads. As result, co-relational alternatives, commonly known as NOSQL (Not Only SQL) databases, are extensively used for Big Data. As the primary focus of NOSQL is on performance, NOSQL databases are directly designed at the physical...

The recent growing interest on highly-available data-intensive applications sparked the need for flexible and portable storage technologies, e.g., NoSQL databases. NoSQL databases have emerged as the solution to handle large quantities of user-generated content still guaranteeing fault-tolerance, availability and scalability. NoSQL databases offer differentiated properties and characteristics a...

NoSQL datastore systems are a new generation of non-relational databases. More than fifty NoSQL systems have been already implemented, each with different characteristics — especially, with different data models and different APIs to access the data. In this paper we describe and compare the data models and operations offered by a number of representative NoSQL datastores, which we have directl...

NoSQL data storage systems have become very popular due to their scalability and ease of use. This paper examines the maturity of security measures for NoSQL databases, addressing their new query and access mechanisms. For example the emergence of new query formats makes the old SQL injection techniques irrelevant, but are NoSQL databases immune to injection in general? The answer is NO. Here w...

T he exponential growth of the Internet has resulted in an explosion of data sources, creating storage and data-usability problems. Furthermore, an increase in the number of data types has created challenges in terms of storing and manipulating unstructured data. These issues have lead companies and open source communities to build new tools, known as NoSQL systems or “key-value-store” systems,...

NoSQL databases are an important component of Big Data for storing and retrieving large volumes of data. Traditional Relational Database Management Systems (RDBMS) use the ACID theorem for data consistency, whereas NoSQL Databases use a non-transactional approach called BASE. RDBMS scale vertically and NoSQL Databases can scale both horizontally (sharding) and vertically. Four types of NoSQL da...

The paper introduces Strudel, a development and execution framework for transactional workloads both on SQL and NoSQL systems. Whereas a rich set of benchmarks and performance analysis platforms have been developed for SQLbased systems (RDBMSs), it is challenging for application developers to evaluate both SQL and NoSQL systems for their specific needs. The Strudel framework, which we have rele...