Retrieve Value Given a set of specific cases, find attributes of those cases. What is the value of aggregation function F over a given set S of data cases? What is the sorted order of a set S of data cases according to their value of attribute A?
Hadoop or an in-memory database? Hadoop and in-memory databases are different technologies, but they overlap. Hadoop is an open source framework for big data analytics.
Hadoop, which has essentially become synonymous with the idea of Big Data, allows an organization to ingest large, highly diverse sources of data and analyze them in ways that are faster and more efficient than is possible with traditional, relational database systems.
It achieves this scale by breaking large workloads into smaller pieces and then distributing them across a cluster of commodity x86 hardware. Hadoop does not do the analytics by itself. Software such as Flume and Sqoop may be used to load data.
Kafka, Spark or Flink are used ingest data or perform streaming analytics.
A host of other tools may be employed to manage, maintain and secure the Hadoop cluster. While tools such as Spark are great at in-memory analytics using streaming data via mini-batches, Spark does not support a database. An in-memory database is a database is designed to run completely in random access memory RAM.
With advances in memory technology and a drop in memory costs, it is now possible to have data sets held in RAM that would have been hard to imagine a few years ago. An in-memory database can easily hold multiple terabytes worth of information in active memory.
The advantage of the in-memory approach is speed. Unlike databases historically, which had to pull data off a disk and process it, the in-memory database can access data at many times the speed that is possible with a spinning disk.
So far, so good.
Hadoop and in-memory databases are different types of technology. One is a software framework. The other is a database designed for specific kinds of hardware. This is where the industry needs to shoulder some responsibility. As vendors and open source communities scramble to achieve dominance in the emerging field of big data, jargon and opinions abound.
It is worth pointing out that you can actually have Hadoop and in-memory databases at the same time. An in-memory database can be part of an extended Hadoop ecosystem.
You can even run Hadoop in-memory. Each has its place. When is it best to use one, the other, or both? The answer revolves around speed, space and cost. In-memory databases are blazingly fast, but they are limited in what they can store.
When sizing in-memory databases, it should also be noted that your raw data is compressed significantly and, in the real world, some types of data are more compressible than others. So, while compression ratios can vary widely based upon data types, cardinality and distribution of data, the most common compression rations which I have seen fall in the 5x to 10x compression range.
Conversely, Hadoop can handle petabytes of information. But, you can put part of it in-memory. There are several Hadoop architectures hybrid in nature which contain both disk and in-memory elements where rapid processing is needed.
Cost will be your other factor in making the decision. Solid state memory is more expensive than equivalent spinning hard disk drives HDDs.
Running an in-memory database will cost more, on a byte by byte basis, then using the commodity disk drives and servers that Hadoop is famous for running.Every project needs someone that can help turn ideas into reality: a business analyst.
Join author and certified business analyst Haydn Thomas as he walks you through the fundamentals of business analysis tools and techniques.
Almost all applications that work with databases (such as database management systems, discussed below) make use of SQL as a way to analyze and manipulate relational data. As its name implies, SQL is a language that can be . Publications.
NIST develops and maintains an extensive collection of standards, guidelines, recommendations, and research on the security and privacy of information and information systems.
In a relational database, all the tables are related by one or more fields, so that it is possible to connect all the tables in the database through the field(s) they have in common.
Figure 1 – Sean Connery is about to take a car trip the hard way – in “You Only Live Twice” – a scene that brings to mind the comparison between Hadoop and in-memory databases.
Big Data (BD), with their potential to ascertain valued insights for enhanced decision-making process, have recently attracted substantial interest from both academics and practitioners.