In-Memory Computing Blogs and Events

IMCPlanet.org presents in-memory computing blogs and events from around the world. Read the latest in-memory computing news here. Submit your RSS feed or post your upcoming events and help the in-memory computing community stay up to date on the latest developments.

Jan
22
2018
Posted by SAP HANA on Monday 22 January 2018, 05:33

Last time we talked about the SAP Web IDE and the editors that you use for Data Warehousing scenarios. But we did not handle two important aspects, which are the main drivers for what is “agile” about this data warehouse approach: the GIT repository, and containers. Containers allow a developer to work in isolation, unobstructed by others. And that is supported by a repository called Git.  
 

Classic DW challenges with one workspace…

Jan
19
2018
Posted by GridGain Systems Blog on Friday 19 January 2018, 10:00

In the previous article, we reviewed and summarized pitfalls of the query-driven data modeling methodology (a.k.a. denormalized data modeling) utilized in Apache Cassandra. Turns out that the methodology prevents us from developing efficient applications without insight into what our queries will be like.

Jan
19
2018
Posted by GridGain Systems Blog on Friday 19 January 2018, 06:00

Happy New Year, everyone! The folks here at GridGain are ready for a fantastic 2018. Here’s an update on what’s happening on the community front over the month or so.

Jan
14
2018
Posted by SAP HANA on Sunday 14 January 2018, 06:38

– Consider Joining the SAP HANA Executive Council –
We all are very aware of how emerging technology is transforming our lives in many ways.
Digitization & hyper-connectivity is entering a new phase and the transformation of books, music and retail has now morphed into healthcare, manufacturing, automotive and other industries.
Whether it is the products we purchase, or how we purchase them, retailing and manufacturing are all getting digitized, connected and smart. Retailing is moving from transactions to 1:1 relationship engagement, while manufacturing is moving from mass production to 3-Dimensional printing of custom products on-demand.
And it is just not products and services, but also how we ourselves are getting digitized. The digital transformation of healthcare is happening now, from generic treatment based on individual disease management to…

Jan
12
2018
Posted by GridGain Systems Blog on Friday 12 January 2018, 10:00

Apache Ignite supports a range of different Application Programming Interfaces (APIs). In this multi-part article series, we will take a more detailed look at how Apache Ignite manages transactions in its key-value API and some of the mechanisms and protocols it supports. In this first part, we will begin with a discussion of the two-phase commit (2PC) protocol and then look at how this works with various types of cluster nodes.

Jan
10
2018
Posted by SAP HANA on Wednesday 10 January 2018, 10:09

2017 was a busy year in enterprise information management at SAP. We released a lot of new and enhanced capabilities across the portfolio to help customers better manage and use their data for digital transformation, cloud, Big Data, the Internet of Things (IoT), and data protection and privacy.
New features include data quality, master data management, content management and information lifecycle management capabilities with enhanced support specifically for SAP S/4HANA®. For example, SAP Master Data Governance on SAP S/4HANA offers consolidation, mass processing, central governance and master data quality analytics to help companies clean and maintain data in SAP S/4HANA.
Updates also include new and expanded support for Amazon Redshift and Amazon Elastic Compute Cloud (Amazon EC2), Microsoft Azure Cloud and SQL Data Warehouse, and Google Cloud…

Jan
09
2018
Posted by IBM IT Infrastructure Blog on Tuesday 9 January 2018, 04:00

Applications don’t stand still. They never have, and they never will… Change is the ONLY constant. Look at a simple and old yet life-sustaining “application” like farming. Tools were once a pair of arms and hands, evolving to a bucket, evolving to a wheelbarrow, evolving to a horse-drawn cart, evolving to however many iterations of human-driven modern tractors, evolving to automation. The process and methods of seeding, irrigating, fertilizing and harvesting have similarly evolved for centuries.
For software applications, the same school of thought applies. There are always new resources. New methodologies. New tools.  New user demands and expectations. As enterprise development teams adapt their business-critical applications to today’s landscape, they face new challenges daily. The modern developer is on an eternal path to wade through all of the new variables to better understand application interdependencies, complexities, and quality across platforms, environments and…

Jan
08
2018
Posted by the morning paper on Monday 8 January 2018, 22:00

The case for learned index structures Kraska et al., arXiv Dec. 2017
Yesterday we looked at the big idea of using learned models in place of hand-coded algorithms for select components of systems software, focusing on indexing within analytical databases. Today we’ll be taking a closer look at range, point, and existence indexes built using this approach. Even with a CPU-based implementation the results are impressive. For example, with integer datasets:

As can be seen, the learned index dominates the B-Tree index in almost all configurations by being up to 3x faster and being up to an order-of-magnitude smaller.

As we left things yesterday, the naive learned index was 2-3x slower! Let’s take a look at what changed to get these kinds of results.

Learned range indexes

Recall that a single learned CDF has difficulty accurately modelling the fine structure of a data…

Jan
08
2018
Posted by Redis Labs on Monday 8 January 2018, 12:21

With the recent security vulnerabilities discovered — Meltdown (CVE-2017-5754) and Spectre (CVE-2017-5753 and CVE-2017-5715) — Redis Labs’ engineering, devops and support teams have been working hard to make sure our cloud services, Redis Cloud (RC) and Redis Cloud Private (RCP), are protected.
As of now, all our RC and RCP clusters on AWS, Azure, GCP and IBM Cloud have been patched by our cloud partners against Meltdown. In addition, some cloud vendors have already managed to mitigate the Spectre’s branch target injection (CVE-2017-5715).
Redis Pack customers:

  • Customers who use Redis Pack on the public clouds mentioned above (and deployed Redis Pack on dedicated…
Jan
08
2018
Posted by GridGain Systems Blog on Monday 8 January 2018, 10:28

The world was rocked after the recent disclosure of the Meltdown and Spectre vulnerabilities that literally affect almost all software ever developed. Both issues are related to the way all modern CPUs are designed and this is why they have opened unprecedented security breaches -- making the software, including GridGain, vulnerable to hacker attacks.

Jan
08
2018
Posted by SAP HANA on Monday 8 January 2018, 09:54

Blackjack
Let me say at the outset, I am not a gambler!  But at my 2nd daughter’s request (she turned 30 on Jan 1), on New Year’s Eve I found myself seated next to her husband, playing black jack at the Biltmore Casino in North Lake Tahoe.  And lo and behold, 2018 started out great – we both beat the dealer and walked away winners…
In early December of 2017, the SAP Cloud Platform team also made a big bet – we wanted to make the customer experience exponentially better on the Cloud Platform website in 2018!  We worked through the holidays and I am happy to introduce for 2018 a…

Jan
08
2018
Posted by GridGain Systems Blog on Monday 8 January 2018, 08:00

MySQL is a widely used open-source relational database management system (RDBMS) and is an excellent solution for many applications, including web-scale applications. However, its architecture has limitations when it comes to big data analytics.

A closer look at the strengths and weaknesses of MySQL reveals several use cases where the RDBMS, powerful though it is, can benefit from some assistance. The following are the five limitations of MySQL in this area:

Jan
07
2018
Posted by the morning paper on Sunday 7 January 2018, 22:00

The case for learned index structures Kraska et al., arXiv Dec. 2017
Welcome to another year of papers on The Morning Paper. With the rate of progress in our field at the moment, I can’t wait to see what 2018 has in store for us!
Two years ago, I started 2016 with a series of papers from the ‘Techniques everyone should know’ chapter of the newly revised ‘Readings in Database Systems.’ So much can happen in two years! I hope it doesn’t take another ten years for us to reach the sixth edition of the ‘Red Book,’ but if it does, in today’s paper choice Kraska et al., are making a strong case for the inclusion of applied machine learning in a future list of essential techniques for database systems. I can’t think of a better way to start the year than wondering about this blend of old and new…

Jan
05
2018
Posted by VoltDB on Friday 5 January 2018, 13:20

The internet is ablaze with articles and talk about hardware security flaws found recently in most modern processors, including chips from Intel and AMD – that is, in the processors used by everyone who runs software to provide a service. In other words, all of VoltDB’s customers. We are actively working on tests of our own and will share more information as we learn about these vulnerabilities and the effects of patching them on VoltDB software.

Background

The vulnerabilities are known as Meltdown and Spectre. In the National Vulnerability Database, they are covered by 3 CVEs:

All Operating System…

Jan
05
2018
Posted by MemSQL Blog on Friday 5 January 2018, 09:00

Traditional data warehouses and databases were built for workloads that manifested 20 years ago. They are sufficient for what they were built to do, but these systems are struggling to meet the demands of modern business with the volume, velocity, and user demand of data. IT departments are being challenged from both ends. On one side, companies want to analyze the deluge of data in real time, or near real time. On the other side, on the consumption end, the need to analyze and get value out of data is increasing exponentially. A decade ago, companies had a handful of analysts who ran reports and a few dashboards. Today, enterprises have armies of data scientists, analysts, and savvy business users wanting to slice and dice the latest data.

The “Flying Car” Dilemma

Companies have invested millions of dollars in procuring and customizing legacy systems. In addition to the capital expense, these companies have spent years hiring and training resources to support and…