All In Memory

Exploring the implications of diskless distributed systems and their open source implementations.

[All In Memory @AllInRam]

X1 instances from EC2: 2TB of in-memory computing (doubling the price of their earlier most expensive machine): https://t.co/oLuF9l1FiE

[All In Memory @AllInRam]

Using Spark with Redis - very interesting development from @redislabs https://t.co/RdHUeGZzAf

[All In Memory @AllInRam]

Better Memory, from CACM, nice overview of NVRAM and its future impact: https://t.co/DTdNhfvRjn

[All In Memory @AllInRam]

Non-volatile Storage: Implications of the Datacenter's Shifting Center: https://t.co/d3K9VML7UH

[All In Memory @AllInRam]

You might want to re-read this every year: What Every Programmer Should Know About Memory, by Ulrich Drepper https://t.co/6wmAK77CHx

[All In Memory @AllInRam]

MarketsAndMarkets predicts the growth of in-memory computing to $23.5 Billion by 2020: http://t.co/E2YrJbWny3 @marketsandmarkets

[All In Memory @AllInRam]

Other big in-memory news from #awsreinvent - the launch of X1 instances with 2TB of RAM - built with dbs like Apache Spark and HANA in mind

[All In Memory @AllInRam]

Amazon SPICE: "columnar storage, in-memory technologies... machine code generation, & data compression" http://t.co/Yxq2UjYTII #awsreinvent

[All In Memory @AllInRam]

Amazon SPICE: Super-fast Parallel In-Memory Computation Engine, backs the newly launched AWS QuickSight. #awsreinvent

[All In Memory @AllInRam]

Amazon could cut prices and launch a new in-memory database at RE Invent: http://t.co/wS3dEjvMu8

[Stephan Ewen @StephanEwen]

These days, "in-memory" can mean (1) using memory-optimized techniques, or (2) being too lazy to implement the out-of-core code paths...

[All In Memory @AllInRam]

"...the server should have anywhere from 512 GB to 1 TB of main memory as a cache for the GPU memory" -@toddmostak http://t.co/SSH5ZGdo77

[All In Memory @AllInRam]

SSD prices in a free fall: http://t.co/YKH1XOZUrw

[All In Memory @AllInRam]

In-memory computing "expected to grow from $2.21 billion in 2013 to $13.23 billion in 2018", compounded growth of 43% http://t.co/LmGdhNGcLn

[All In Memory @AllInRam]

Feral Concurrency Control: http://t.co/mnlM9GbAS5 from @pbailis at SIGMOD2015

[Kay Ousterhout @kayousterhout]

Thanks to everyone who came to my talk at @spark_summit about Spark performance! Slides now available here: http://t.co/lIFL3iAMCY

[All In Memory @AllInRam]

MLlib: machine learning on spark: http://t.co/ErEtK8LIX1

[All In Memory @AllInRam]

Interview with @matei_zaharia, by @kdnuggets http://t.co/sKSZqV3vGT

[All In Memory @AllInRam]

Investigating @ApacheSpark's performance: http://t.co/g0llIqAEhq

[All In Memory @AllInRam]

DBx1000 - a single-node OLTP DBMS to develop concurrency schemes on future systems with many, many cores: http://t.co/w4UTkbU2kW