|By Nikita Ivanov||
|December 29, 2014 12:00 PM EST||
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
Skip to conclusion to get the bottom line.
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
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.
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.
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 Grid||In-Memory Database|
|Existing RDBMS||Unchanged||Changed or Replaced|
When people aren’t talking about VMs and containers, they’re talking about serverless architecture. Serverless is about no maintenance. It means you are not worried about low-level infrastructural and operational details. An event-driven serverless platform is a great use case for IoT. In his session at @ThingsExpo, Animesh Singh, an STSM and Lead for IBM Cloud Platform and Infrastructure, will detail how to build a distributed serverless, polyglot, microservices framework using open source tec...
Jun. 27, 2016 08:30 PM EDT Reads: 324
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 ...
Jun. 27, 2016 07:45 PM EDT Reads: 346
Basho Technologies has announced the latest release of Basho Riak TS, version 1.3. Riak TS is an enterprise-grade NoSQL database optimized for Internet of Things (IoT). The open source version enables developers to download the software for free and use it in production as well as make contributions to the code and develop applications around Riak TS. Enhancements to Riak TS make it quick, easy and cost-effective to spin up an instance to test new ideas and build IoT applications. In addition to...
Jun. 27, 2016 05:15 PM EDT Reads: 356
Presidio has received the 2015 EMC Partner Services Quality Award from EMC Corporation for achieving outstanding service excellence and customer satisfaction as measured by the EMC Partner Services Quality (PSQ) program. Presidio was also honored as the 2015 EMC Americas Marketing Excellence Partner of the Year and 2015 Mid-Market East Partner of the Year. The EMC PSQ program is a project-specific survey program designed for partners with Service Partner designations to solicit customer feedbac...
Jun. 27, 2016 03:15 PM EDT Reads: 351
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.
Jun. 27, 2016 03:00 PM EDT Reads: 1,159
Machine Learning helps make complex systems more efficient. By applying advanced Machine Learning techniques such as Cognitive Fingerprinting, wind project operators can utilize these tools to learn from collected data, detect regular patterns, and optimize their own operations. In his session at 18th Cloud Expo, Stuart Gillen, Director of Business Development at SparkCognition, discussed how research has demonstrated the value of Machine Learning in delivering next generation analytics to imp...
Jun. 27, 2016 03:00 PM EDT Reads: 760
It is one thing to build single industrial IoT applications, but what will it take to build the Smart Cities and truly society changing applications of the future? The technology won’t be the problem, it will be the number of parties that need to work together and be aligned in their motivation to succeed. In his Day 2 Keynote at @ThingsExpo, Henrik Kenani Dahlgren, Portfolio Marketing Manager at Ericsson, discussed how to plan to cooperate, partner, and form lasting all-star teams to change t...
Jun. 27, 2016 02:45 PM EDT Reads: 1,232
In his keynote at 18th Cloud Expo, Andrew Keys, Co-Founder of ConsenSys Enterprise, provided an overview of the evolution of the Internet and the Database and the future of their combination – the Blockchain. Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life sett...
Jun. 27, 2016 02:30 PM EDT Reads: 1,237
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...
Jun. 27, 2016 12:00 PM EDT Reads: 847
Connected devices and the industrial internet are growing exponentially every year with Cisco expecting 50 billion devices to be in operation by 2020. In this period of growth, location-based insights are becoming invaluable to many businesses as they adopt new connected technologies. Knowing when and where these devices connect from is critical for a number of scenarios in supply chain management, disaster management, emergency response, M2M, location marketing and more. In his session at @Th...
Jun. 27, 2016 10:00 AM EDT Reads: 1,055
The cloud market growth today is largely in public clouds. While there is a lot of spend in IT departments in virtualization, these aren’t yet translating into a true “cloud” experience within the enterprise. What is stopping the growth of the “private cloud” market? In his general session at 18th Cloud Expo, Nara Rajagopalan, CEO of Accelerite, explored the challenges in deploying, managing, and getting adoption for a private cloud within an enterprise. What are the key differences between wh...
Jun. 27, 2016 09:30 AM EDT Reads: 899
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, wh...
Jun. 27, 2016 07:30 AM EDT Reads: 1,076
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 expected in the amount of information being processed, managed, analyzed, and acted upon by enterprise IT. This amazing is not part of some distant future - it is happening today. One report shows a 650% increase in enterprise data by 2020. Other estimates are even higher....
Jun. 26, 2016 05:00 PM EDT Reads: 1,326
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.
Jun. 26, 2016 05:00 PM EDT Reads: 1,244
Internet of @ThingsExpo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 19th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago. All major researchers estimate there will be tens of billions devices - comp...
Jun. 26, 2016 04:00 PM EDT Reads: 1,299
19th Cloud Expo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Meanwhile, 94% of enterpri...
Jun. 26, 2016 04:00 PM EDT Reads: 1,367
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...
Jun. 26, 2016 12:00 PM EDT Reads: 1,376
The 19th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportuni...
Jun. 26, 2016 12:00 PM EDT Reads: 1,315
Internet of @ThingsExpo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with the 19th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world and ThingsExpo Silicon Valley Call for Papers is now open.
Jun. 26, 2016 12:00 PM EDT Reads: 1,153
Cognitive Computing is becoming the foundation for a new generation of solutions that have the potential to transform business. Unlike traditional approaches to building solutions, a cognitive computing approach allows the data to help determine the way applications are designed. This contrasts with conventional software development that begins with defining logic based on the current way a business operates. In her session at 18th Cloud Expo, Judith S. Hurwitz, President and CEO of Hurwitz & ...
Jun. 25, 2016 03:00 PM EDT Reads: 1,652