Codetown ::: a software developer's community
I don't clearly catch the difference betwenn these two concept. Someone told me that the essential différence is that the cloud computing give you a large space of storage and the grig give more advantages than storage, we can profit to much power with this last.
Does any one know more clearly these two concept; and tell us?
Tags:
I don't claim to be the expert, but the difference is (I think) in use.
Grid represents a scalable framework. You write your algorithm and your code and use as much computing power as you wallet can afford. (Useful as some work can be highly parallelizable) .
Cloud computing offers storage (true) but it's also represents the applications as well. Ideally with cloud computing, you don't need to have certain applications on your desktop - as long as you can hit the cloud, you can get, update, and use your data.
Thanks thomas;
What I got :
Grid - much computing power and can be highly parallelizable
Cloud - Storage and dont need to have certain applications on your desktop ( that's just like server application?)
Someone can tell us more?
I think if you look at the history, you will understand some difference.
In my own experience, the grid began with Oracle using it as a type of metadatabase, which would point to multiple databases residing on different but uniform hardware systems. So if a company had multiple unix boxes and needed to increase the size of their database, instead of purchasing additional hardware they could implement the grid database and combine their multiple unix servers into one database resource.
Cloud is much more in terms of it offering not only a database, but also an entire server including the operating system.
The cloud exposes an operating system, whereas a grid exposes a database.
But I am no buzz word expert so I might be wrong.
I just talked to a buddy about this, essentially the Oracle Grid product is differant because it runs the DB in memory. So access times are a lot quicker. I don't think it is really a matter of Vs. so much as Grid computing is a way to handle db transactions in a faster way.
He said their grid servers had something like 72gbs of ram. Freaking crazy
Please Bradley, wha do you think about Jackie's reaction?
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
Check out the Codetown Jobs group.

This week's Java roundup for May 18th, 2026, features news highlighting: GA releases of WildFly 40, Micronaut 5.0, Maven Embedded GlassFish Plugin 8.0 and Apache Fory 1.0; the May 2026 edition of Open Liberty; point releases of Gatherers4j, Apache and Kafka; and the seventh milestone release of Spring AI 2.0.
By Michael Redlich
Microsoft has introduced a new AI-driven vulnerability discovery system called MDASH, a multi-model agentic security platform designed to automate large-scale code auditing across Windows and other Microsoft software environments. The system combines more than 100 specialized AI agents that work together to scan, validate, debate, and prove vulnerabilities across complex codebases.
By Robert Krzaczyński
Schema proliferation builds slowly and gets expensive fast. One schema per event type feels right until there are ten tables, union queries spanning all of them, and a single field rename touching every schema. Discriminator-based schema consolidation collapses that to two tables, turning multi-table unions into a single query, while new variants are additive and don't break existing consumers.
By Spoorthi Basu
Sergiu Petean discusses the strategic journey of evolving DevOps into platform engineering within heavily regulated enterprise environments. He explains how to maximize efficiency using dynamic reference architectures, align platform KPIs directly with board-level business goals, reduce cognitive load via custom team topologies, and maintain innovation sovereignty through open-source technology.
By Sergiu PeteanGunnar Morling, technologist at Confluent and Java Champion, shares his experiences with building high-performance applications in Java, especially in the data space. He shares insights from experiments with building durable execution engines, bootstrapping, and AI natively developing Apache Hardwood - a minimal dependencies Java parser for Apache Parquet.
By Gunnar Morling
© 2026 Created by Michael Levin.
Powered by