Welcome!

Java IoT Authors: Pat Romanski, Liz McMillan, Elizabeth White, Automic Blog, Jnan Dash

Related Topics: @BigDataExpo, Java IoT, Linux Containers, Agile Computing, @CloudExpo, Cloud Security

@BigDataExpo: Blog Post

In-Memory Database vs. In-Memory Data Grid By @GridGain | @CloudExpo [#BigData]

It's easy to start with technical differences between the two categories

A few months ago, I spoke at the conference where I explained the difference between caching and an in-memory data grid. Today, having realized that many people are also looking to better understand the difference between two major categories in in-memory computing: In-Memory Database and In-Memory Data Grid, I am sharing the succinct version of my thinking on this topic - thanks to a recent analyst call that helped to put everything in place :)

TL;DR

Skip to conclusion to get the bottom line.

Nomenclature
Let's clarify the naming and buzzwords first. In-Memory Database (IMDB) is a well-established category name and it is typically used unambiguously.

It is important to note that there is a new crop of traditional databases with serious In-Memory "options". That includes MS SQL 2014, Oracle's Exalytics and Exadata, and IBM DB2 with BLU offerings. The line is blurry between these and the new pure In-Memory Databases, and for the simplicity I'll continue to call them In-Memory Databases.

In-Memory Data Grids (IMDGs) are sometimes (but not very frequently) called In-Memory NoSQL/NewSQL Databases. Although the latter can be more accurate in some case - I am going to use the In-Memory Data Grid term in this article, as it tends to be the more widely used term.

Note that there are also In-Memory Compute Grids and In-Memory Computing Platforms that include or augment many of the features of In-Memory Data Grids and In-Memory Databases.

Confusing, eh? It is... and for consistency - going forward we'll just use these terms for the two main categories:

  • In-Memory Database
  • In-Memory Data Grid

Tiered Storage
It is also important to nail down what we mean by "In-Memory". Surprisingly - there's a lot of confusion here as well as some vendors refer to SSDs, Flash-on-PCI, Memory Channel Storage, and, of course, DRAM as "In-Memory".

In reality, most vendors support a Tiered Storage Model where some portion of the data is stored in DRAM (the fastest storage but with limited capacity) and then it gets overflown to a verity of flash or disk devices (slower but with more capacity) - so it is rarely a DRAM-only or Flash-only product. However, it's important to note that most products in both categories are often biased towards mostly DRAM or mostly flash/disk storage in their architecture.

Bottom line is that products vary greatly in what they mean by "In-Memory" but in the end they all have a significant "In-Memory" component.

Technical Differences
It's easy to start with technical differences between the two categories.

Most In-Memory Databases are your father's RDBMS that store data "in memory" instead of disk. That's practically all there's to it. They provide good SQL support with only a modest list of unsupported SQL features, shipped with ODBC/JDBC drivers and can be used in place of existing RDBMS often without significant changes.

In-Memory Data Grids typically lack full ANSI SQL support but instead provide MPP-based (Massively Parallel Processing) capabilities where data is spread across large cluster of commodity servers and processed in explicitly parallel fashion. The main access pattern is key/value access, MapReduce, various forms of HPC-like processing, and a limited distributed SQL querying and indexing capabilities.

It is important to note that there is a significant crossover from In-Memory Data Grids to In-Memory Databases in terms of SQL support. GridGain, for example, provides pretty serious and constantly growing support for SQL including pluggable indexing, distributed joins optimization, custom SQL functions, etc.

Speed Only vs. Speed + Scalability
One of the crucial differences between In-Memory Data Grids and In-Memory Databases lies in the ability to scale to hundreds and thousands of servers. That is the In-Memory Data Grid's inherent capability for such scale due to their MPP architecture, and the In-Memory Database's explicit inability to scale due to fact that SQL joins, in general, cannot be efficiently performed in a distribution context.

It's one of the dirty secrets of In-Memory Databases: one of their most useful features, SQL joins, is also is their Achilles heel when it comes to scalability. This is the fundamental reason why most existing SQL databases (disk or memory based) are based on vertically scalable SMP (Symmetrical Processing) architecture unlike In-Memory Data Grids that utilize the much more horizontally scalable MPP approach.

It's important to note that both In-Memory Data Grids and In-Memory Database can achieve similar speed in a local non-distributed context. In the end - they both do all processing in memory.

But only In-Memory Data Grids can natively scale to hundreds and thousands of nodes providing unprecedented scalability and unrivaled throughput.

Replace Database vs. Change Application
Apart from scalability, there is another difference that is important for uses cases where In-Memory Data Grids or In-Memory Database are tasked with speeding up existing systems or applications.

An In-Memory Data Grid always works with an existing database providing a layer of massively distributed in-memory storage and processing between the database and the application. Applications then rely on this layer for super-fast data access and processing. Most In-Memory Data Grids can seamlessly read-through and write-through from and to databases, when necessary, and generally are highly integrated with existing databases.

In exchange - developers need to make some changes to the application to take advantage of these new capabilities. The application no longer "talks" SQL only, but needs to learn how to use MPP, MapReduce or other techniques of data processing.

In-Memory Databases provide almost a mirror opposite picture: they often requirereplacing your existing database (unless you use one of those In-Memory "options" to temporary boost your database performance) - but will demand significantly less changes to the application itself as it will continue to rely on SQL (albeit a modified dialect of it).

In the end, both approaches have their advantages and disadvantages, and they may often depend in part on organizational policies and politics as much as on their technical merits.

Conclusion
The bottom line should be pretty clear by now.

If you are developing a green-field, brand new system or application the choice is pretty clear in favor of In-Memory Data Grids. You get the best of the two worlds: you get to work with the existing databases in your organization where necessary, and enjoy tremendous performance and scalability benefits of In-Memory Data Grids - both of which are highly integrated.

If you are, however, modernizing your existing enterprise system or application the choice comes down to this:

You will want to use an In-Memory Database if the following applies to you:

  • You can replace or upgrade your existing disk-based RDBMS
  • You cannot make changes to your applications
  • You care about speed, but don't care as much about scalability

In other words - you boost your application's speed by replacing or upgrading RDBMS without significantly touching the application itself.

On the other hand, you want to use an In-Memory Data Grid if the following applies to you:

  • You cannot replace your existing disk-based RDBMS
  • You can make changes to (the data access subsystem of) your application
  • You care about speed and especially about scalability, and don't want to trade one for the other

In other words - with an In-Memory Data Grid you can boost your application's speed and provide massive scale by tweaking the application, but without making changes to your existing database.

It can be summarized it in the following table:


In-Memory Data GridIn-Memory Database
Existing Application Changed Unchanged
Existing RDBMS Unchanged Changed or Replaced
Speed Yes Yes
Max. Scalability Yes No

More Stories By Nikita Ivanov

Nikita Ivanov is founder and CEO of GridGain Systems, started in 2007 and funded by RTP Ventures and Almaz Capital. Nikita has led GridGain to develop advanced and distributed in-memory data processing technologies – the top Java in-memory computing platform starting every 10 seconds around the world today.

Nikita has over 20 years of experience in software application development, building HPC and middleware platforms, contributing to the efforts of other startups and notable companies including Adaptec, Visa and BEA Systems. Nikita was one of the pioneers in using Java technology for server side middleware development while working for one of Europe’s largest system integrators in 1996.

He is an active member of Java middleware community, contributor to the Java specification, and holds a Master’s degree in Electro Mechanics from Baltic State Technical University, Saint Petersburg, Russia.

@ThingsExpo Stories
IoT offers a value of almost $4 trillion to the manufacturing industry through platforms that can improve margins, optimize operations & drive high performance work teams. By using IoT technologies as a foundation, manufacturing customers are integrating worker safety with manufacturing systems, driving deep collaboration and utilizing analytics to exponentially increased per-unit margins. However, as Benoit Lheureux, the VP for Research at Gartner points out, “IoT project implementers often ...
The Jevons Paradox suggests that when technological advances increase efficiency of a resource, it results in an overall increase in consumption. Writing on the increased use of coal as a result of technological improvements, 19th-century economist William Stanley Jevons found that these improvements led to the development of new ways to utilize coal. In his session at 19th Cloud Expo, Mark Thiele, Chief Strategy Officer for Apcera, will compare the Jevons Paradox to modern-day enterprise IT, e...
Complete Internet of Things (IoT) embedded device security is not just about the device but involves the entire product’s identity, data and control integrity, and services traversing the cloud. A device can no longer be looked at as an island; it is a part of a system. In fact, given the cross-domain interactions enabled by IoT it could be a part of many systems. Also, depending on where the device is deployed, for example, in the office building versus a factory floor or oil field, security ha...
SYS-CON Events announced today the Enterprise IoT Bootcamp, being held November 1-2, 2016, in conjunction with 19th Cloud Expo | @ThingsExpo at the Santa Clara Convention Center in Santa Clara, CA. Combined with real-world scenarios and use cases, the Enterprise IoT Bootcamp is not just based on presentations but with hands-on demos and detailed walkthroughs. We will introduce you to a variety of real world use cases prototyped using Arduino, Raspberry Pi, BeagleBone, Spark, and Intel Edison. Y...
Is your aging software platform suffering from technical debt while the market changes and demands new solutions at a faster clip? It’s a bold move, but you might consider walking away from your core platform and starting fresh. ReadyTalk did exactly that. In his General Session at 19th Cloud Expo, Michael Chambliss, Head of Engineering at ReadyTalk, will discuss why and how ReadyTalk diverted from healthy revenue and over a decade of audio conferencing product development to start an innovati...
Fifty billion connected devices and still no winning protocols standards. HTTP, WebSockets, MQTT, and CoAP seem to be leading in the IoT protocol race at the moment but many more protocols are getting introduced on a regular basis. Each protocol has its pros and cons depending on the nature of the communications. Does there really need to be only one protocol to rule them all? Of course not. In his session at @ThingsExpo, Chris Matthieu, co-founder and CTO of Octoblu, walk you through how Oct...
SYS-CON Events announced today that Bsquare has been named “Silver Sponsor” of SYS-CON's @ThingsExpo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. For more than two decades, Bsquare has helped its customers extract business value from a broad array of physical assets by making them intelligent, connecting them, and using the data they generate to optimize business processes.
Identity is in everything and customers are looking to their providers to ensure the security of their identities, transactions and data. With the increased reliance on cloud-based services, service providers must build security and trust into their offerings, adding value to customers and improving the user experience. Making identity, security and privacy easy for customers provides a unique advantage over the competition.
There are several IoTs: the Industrial Internet, Consumer Wearables, Wearables and Healthcare, Supply Chains, and the movement toward Smart Grids, Cities, Regions, and Nations. There are competing communications standards every step of the way, a bewildering array of sensors and devices, and an entire world of competing data analytics platforms. To some this appears to be chaos. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, Bradley Holt, Developer Advocate a...
If you’re responsible for an application that depends on the data or functionality of various IoT endpoints – either sensors or devices – your brand reputation depends on the security, reliability, and compliance of its many integrated parts. If your application fails to deliver the expected business results, your customers and partners won't care if that failure stems from the code you developed or from a component that you integrated. What can you do to ensure that the endpoints work as expect...
So, you bought into the current machine learning craze and went on to collect millions/billions of records from this promising new data source. Now, what do you do with them? Too often, the abundance of data quickly turns into an abundance of problems. How do you extract that "magic essence" from your data without falling into the common pitfalls? In her session at @ThingsExpo, Natalia Ponomareva, Software Engineer at Google, provided tips on how to be successful in large scale machine learning...
If you had a chance to enter on the ground level of the largest e-commerce market in the world – would you? China is the world’s most populated country with the second largest economy and the world’s fastest growing market. It is estimated that by 2018 the Chinese market will be reaching over $30 billion in gaming revenue alone. Admittedly for a foreign company, doing business in China can be challenging. Often changing laws, administrative regulations and the often inscrutable Chinese Interne...
In his general session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed cloud as a ‘better data center’ and how it adds new capacity (faster) and improves application availability (redundancy). The cloud is a ‘Dynamic Tool for Dynamic Apps’ and resource allocation is an integral part of your application architecture, so use only the resources you need and allocate /de-allocate resources on the fly.
Enterprise IT has been in the era of Hybrid Cloud for some time now. But it seems most conversations about Hybrid are focused on integrating AWS, Microsoft Azure, or Google ECM into existing on-premises systems. Where is all the Private Cloud? What do technology providers need to do to make their offerings more compelling? How should enterprise IT executives and buyers define their focus, needs, and roadmap, and communicate that clearly to the providers?
SYS-CON Events announced today that Commvault, a global leader in enterprise data protection and information management, has been named “Bronze Sponsor” of SYS-CON's 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Commvault is a leading provider of data protection and information management solutions, helping companies worldwide activate their data to drive more value and business insight and to transform moder...
The many IoT deployments around the world are busy integrating smart devices and sensors into their enterprise IT infrastructures. Yet all of this technology – and there are an amazing number of choices – is of no use without the software to gather, communicate, and analyze the new data flows. Without software, there is no IT. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists will look at the protocols that communicate data and the emerging data analy...
Digital innovation is the next big wave of business transformation based on digital technologies of which IoT and Big Data are key components, For example: Business boundary innovation is a challenge to excavate third-party business value using IoT and BigData, like Nest Business structure innovation may propose re-building business structure from scratch, as Uber does in the taxicab industry The social model innovation is also a big challenge to the new social architecture with the design fr...
Data is an unusual currency; it is not restricted by the same transactional limitations as money or people. In fact, the more that you leverage your data across multiple business use cases, the more valuable it becomes to the organization. And the same can be said about the organization’s analytics. In his session at 19th Cloud Expo, Bill Schmarzo, CTO for the Big Data Practice at EMC, will introduce a methodology for capturing, enriching and sharing data (and analytics) across the organizati...
IoT is fundamentally transforming the auto industry, turning the vehicle into a hub for connected services, including safety, infotainment and usage-based insurance. Auto manufacturers – and businesses across all verticals – have built an entire ecosystem around the Connected Car, creating new customer touch points and revenue streams. In his session at @ThingsExpo, Macario Namie, Head of IoT Strategy at Cisco Jasper, will share real-world examples of how IoT transforms the car from a static p...
There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. Big Data at Cloud Expo - to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA - has announced its Call for Papers is open. Cloud computing is being adopted in one form or another by 94% of enterprises today. Tens of billions of new devices are being connected to The Internet of Things. And Big Data is driving this bus. An exponential increase is...