Welcome!

@DXWorldExpo Authors: Pat Romanski, Liz McMillan, Roger Strukhoff, Elizabeth White, Mark Herring

Related Topics: @DXWorldExpo, Java IoT, Microservices Expo, Containers Expo Blog, @CloudExpo, SDN Journal

@DXWorldExpo: Article

Columnar vs. Key-Value Storage Models

Pay attention to specific configuration and tuning around three points

What are the performance differences between in-memory columnar databases like SAP HANA and GridGain's In-Memory Database (IMDB) utilizing distributed key-value storage? This questions comes up regularly in conversations with our customers and the answer is not very obvious.

Storage Models
First off, let's clearly state that we are talking about storage model only and its implications on performance for various use cases. It's important to note that:

  • Storage model doesn't dictate of preclude a particular transactionality or consistency guarantees; there are columnar databases that support ACID (HANA) and those that don't (HBase); there are distributed key-value databases that support ACID (GridGain) and those that don't (for example, Riak and memcached).
  • Storage model doesn't dictate specific query language; using above examples - GridGain and HANA support SQL - HBase, for example, doesn't.

Unlike transactionality and query language - performance considerations, however, are not that straightforward.

Note also: SAP HANA has pluggable storage model and experimental row-based storage implementation. We'll concentrate on columnar storage that apparently accounts for all HANA usage at this point.

HANA's Columnar Storage Model
Let's recall what columnar storage model entails in general and note its HANA specifics.

Some of its stand out characteristics include:

  • Data in columnar model is kept in column (vs. rows as in row storage models).
  • Since data in a single column is almost always homogeneous it's frequently compressed for storage (especially in in-memory systems like HANA).
  • Aggregate functions (i.e. column functions) are very fast on columnar data model since the entire column can be fetched very quickly and effectively indexed.
  • Inserts, updates and row functions, however, are significantly slower than their row-based counterparts as a trade-off of columnar approach (inserting a row leads to multiple columns inserts). Because of this characteristic - columnar databased typically used in R/OLAP scenario (where data doesn't change) and very rarely in OLTP use cases (where data changes frequently).
  • Since columnar storage is fairly compact it doesn't generally require distribution (i.e. data partitioning) to store large datasets - the entire database can often be logically stored in memory of a single server. HANA, however, provides comprehensive support for data partitioning.

It is important to emphasize that columnar storage model is ideally suited for very compact memory utilization for the two main reasons:

  • Columnar model is a naturally fit for compression which often provides for dramatic reduction in memory consumption.
  • Since column-based functions are very fast - there is no need for materialized views for aggregated values in exchange for simply computing necessary values on the fly; this leads to significantly reduced memory footprint as well.

GridGain's IMDB Key-Value Storage Model
Key-value (KV) storage model is less defined than its columnar counterpart and usually involves a fair amount of vendor specifics.

Historically, there are two schools of KV storage models:

  • Traditional (examples include Riak, memcached, Redis). The common characteristic of these systems is a raw, language independent storage format for the keys and values.
  • Data Grid (examples include GridGain IMDB, GigaSpaces, Coherence). The common trait of these systems is the reliance on JVM as underlying runtime platform, and treating keys and values as user-defined JVM objects.

GridGain's IMDB belongs to Data Grid branch of KV storage models. Some of its key characteristics are:

  • Data is stored in a set of distributed maps (a.k.a. dictionaries or caches); in a simple approximation you can think of a value as a row in row-based model, and a key as that row's primary key. Following this analogy a single KV map can be approximated as row-based table with automatic primary key index.
  • Keys and values are represented as user-defined JVM objects and therefore no automatic compression can be performed.
  • Data distribution is designed from the ground up. Data is partitioned across the cluster mitigating, in part, lack of compression. Unlike HANA - data partitioning is mandatory.
  • MapReduce is the main API for data processing (SQL is supported as well).
  • Strong affinity and co-location semantics provided by default.
  • No bias towards aggregate or row-based processing performance and therefore no bias towards either OLAP or OLTP applicability.

Performance Considerations
It is somewhat expected that for heavy transactional processing GridGain will provide overall better performance in most cases:

  • Columnar model is rather inefficient in updating or inserting values in multiple columns.
  • Transactional locking is also less efficient in columnar model.
  • Required de-compression and re-compression further degrades performance.
  • KV storage model, on the other hand, provides an ideal model for individual updates as individual objects can be accessed, locked and updated very effectively.
  • Lack of compression in GridGain IMDB makes updates go even faster than in columnar model with compression.

As an example, GridGain just won a public tender for one of the biggest financial institutions in the world achieving 1 billion transactional updates per second on 10 commodity blades costing less than $25K all together. That transactional performance and associated TCO is clearly not the territory any columnar database can approach.

For OLAP workloads the picture is less obvious. HANA is heavily biased towards OLAP processing, and GridGain IMDB is neutral towards it. Both GridGain IMDB and SAP HANA provides comprehensive data partitioning capabilities and allow for processing parallelization - MPP traits necessary for scale out OLAP processing. I believe the actual difference observed by the customers will be driven primarily by three factors rooted deeply in differences between columnar and KV implementations in respective products:

  • Optimizations around data affinity and co-location.
  • Optimizations around the distribution overhead.
  • Optimizations around indexing of partitioned data.

Unfortunately - there's no way to provide any generalized guidance on performance difference here... We always recommend to try both in your particular scenario, pay attention to specific configuration and tuning around three points mentioned above - and see what results you'll get. It does take time and resources - but you may be surprised by your findings!

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.

@BigDataExpo Stories
Smart cities have the potential to change our lives at so many levels for citizens: less pollution, reduced parking obstacles, better health, education and more energy savings. Real-time data streaming and the Internet of Things (IoT) possess the power to turn this vision into a reality. However, most organizations today are building their data infrastructure to focus solely on addressing immediate business needs vs. a platform capable of quickly adapting emerging technologies to address future ...
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, whic...
Cloud Expo | DXWorld Expo have announced the conference tracks for Cloud Expo 2018. Cloud Expo will be held June 5-7, 2018, at the Javits Center in New York City, and November 6-8, 2018, at the Santa Clara Convention Center, Santa Clara, CA. Digital Transformation (DX) is a major focus with the introduction of DX Expo within the program. Successful transformation requires a laser focus on being data-driven and on using all the tools available that enable transformation if they plan to survive ov...
In his general session at 21st Cloud Expo, Greg Dumas, Calligo’s Vice President and G.M. of US operations, discussed the new Global Data Protection Regulation and how Calligo can help business stay compliant in digitally globalized world. Greg Dumas is Calligo's Vice President and G.M. of US operations. Calligo is an established service provider that provides an innovative platform for trusted cloud solutions. Calligo’s customers are typically most concerned about GDPR compliance, application p...
Digital transformation is about embracing digital technologies into a company's culture to better connect with its customers, automate processes, create better tools, enter new markets, etc. Such a transformation requires continuous orchestration across teams and an environment based on open collaboration and daily experiments. In his session at 21st Cloud Expo, Alex Casalboni, Technical (Cloud) Evangelist at Cloud Academy, explored and discussed the most urgent unsolved challenges to achieve f...
Continuous Delivery makes it possible to exploit findings of cognitive psychology and neuroscience to increase the productivity and happiness of our teams. In his session at 22nd Cloud Expo | DXWorld Expo, Daniel Jones, CTO of EngineerBetter, will answer: How can we improve willpower and decrease technical debt? Is the present bias real? How can we turn it to our advantage? Can you increase a team’s effective IQ? How do DevOps & Product Teams increase empathy, and what impact does empath...
DevOps promotes continuous improvement through a culture of collaboration. But in real terms, how do you: Integrate activities across diverse teams and services? Make objective decisions with system-wide visibility? Use feedback loops to enable learning and improvement? With technology insights and real-world examples, in his general session at @DevOpsSummit, at 21st Cloud Expo, Andi Mann, Chief Technology Advocate at Splunk, explored how leading organizations use data-driven DevOps to close th...
As many know, the first generation of Cloud Management Platform (CMP) solutions were designed for managing virtual infrastructure (IaaS) and traditional applications. But that's no longer enough to satisfy evolving and complex business requirements. In his session at 21st Cloud Expo, Scott Davis, Embotics CTO, explored how next-generation CMPs ensure organizations can manage cloud-native and microservice-based application architectures, while also facilitating agile DevOps methodology. He expla...
To get the most out of their data, successful companies are not focusing on queries and data lakes, they are actively integrating analytics into their operations with a data-first application development approach. Real-time adjustments to improve revenues, reduce costs, or mitigate risk rely on applications that minimize latency on a variety of data sources. In his session at @BigDataExpo, Jack Norris, Senior Vice President, Data and Applications at MapR Technologies, reviewed best practices to ...
"Digital transformation - what we knew about it in the past has been redefined. Automation is going to play such a huge role in that because the culture, the technology, and the business operations are being shifted now," stated Brian Boeggeman, VP of Alliances & Partnerships at Ayehu, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
SYS-CON Events announced today that Synametrics Technologies will exhibit at SYS-CON's 22nd International Cloud Expo®, which will take place on June 5-7, 2018, at the Javits Center in New York, NY. Synametrics Technologies is a privately held company based in Plainsboro, New Jersey that has been providing solutions for the developer community since 1997. Based on the success of its initial product offerings such as WinSQL, Xeams, SynaMan and Syncrify, Synametrics continues to create and hone inn...
"Evatronix provides design services to companies that need to integrate the IoT technology in their products but they don't necessarily have the expertise, knowledge and design team to do so," explained Adam Morawiec, VP of Business Development at Evatronix, in this SYS-CON.tv interview at @ThingsExpo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
The 22nd International Cloud Expo | 1st DXWorld Expo has announced that its Call for Papers is open. Cloud Expo | DXWorld Expo, to be held June 5-7, 2018, at the Javits Center in New York, NY, brings together Cloud Computing, Digital Transformation, Big Data, Internet of Things, DevOps, Machine Learning 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 busin...
In his Opening Keynote at 21st Cloud Expo, John Considine, General Manager of IBM Cloud Infrastructure, led attendees through the exciting evolution of the cloud. He looked at this major disruption from the perspective of technology, business models, and what this means for enterprises of all sizes. John Considine is General Manager of Cloud Infrastructure Services at IBM. In that role he is responsible for leading IBM’s public cloud infrastructure including strategy, development, and offering m...
Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration an...
No hype cycles or predictions of a gazillion things here. IoT is here. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen. In his session at @ThingsExpo, Jay Mason, an Associate Partner of Analytics, IoT & Cybersecurity at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He also discussed the evaluation of communication standards and IoT messaging protocols, data...
Recently, REAN Cloud built a digital concierge for a North Carolina hospital that had observed that most patient call button questions were repetitive. In addition, the paper-based process used to measure patient health metrics was laborious, not in real-time and sometimes error-prone. In their session at 21st Cloud Expo, Sean Finnerty, Executive Director, Practice Lead, Health Care & Life Science at REAN Cloud, and Dr. S.P.T. Krishnan, Principal Architect at REAN Cloud, discussed how they built...
In a recent survey, Sumo Logic surveyed 1,500 customers who employ cloud services such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). According to the survey, a quarter of the respondents have already deployed Docker containers and nearly as many (23 percent) are employing the AWS Lambda serverless computing framework. It’s clear: serverless is here to stay. The adoption does come with some needed changes, within both application development and operations. Tha...
SYS-CON Events announced today that Evatronix will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Evatronix SA offers comprehensive solutions in the design and implementation of electronic systems, in CAD / CAM deployment, and also is a designer and manufacturer of advanced 3D scanners for professional applications.
The “Digital Era” is forcing us to engage with new methods to build, operate and maintain applications. This transformation also implies an evolution to more and more intelligent applications to better engage with the customers, while creating significant market differentiators. In both cases, the cloud has become a key enabler to embrace this digital revolution. So, moving to the cloud is no longer the question; the new questions are HOW and WHEN. To make this equation even more complex, most ...