Oren Eini

aka Ayende Rahien

Oren Eini

CEO of RavenDB

a NoSQL Open Source Document Database

Get in touch with me:

oren@ravendb.net

+972 52-548-6969

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Deep Dive into RavenDB webinars

Jun 16 2020

Webinar recordingUsing RavenDB as a queuing infrastructure

time to read 1 min | 40 words

The recording for using RavenDB as queueing infrastructure is ready.

Today I’m going to be talking about ACID and how it plays out in RavenDB and in MongoDB.

Tweet Share Share 2 comments

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More posts in "Webinar recording" series:

(26 Aug 2022) Modeling Relationships and Hierarchies in a Document Database
(26 Jul 2022) RavenDB & Messaging Transactions
(24 May 2021) The Rewards of Escaping the Relational Mindset
(15 Jan 2021) Filtered Replication in RavenDB
(04 Dec 2020) RavenDB & Your Operations Team
(28 Oct 2020) Advanced Search Scenarios in RavenDB
(27 Aug 2020) The App that Guarantees You're Going Out This Saturday Night
(10 Jul 2020) Multi tenancy with RavenDB
(02 Jul 2020) Practical indexing with RavenDB
(16 Jun 2020) Using RavenDB as a queuing infrastructure
(09 Jun 2020) RavenDB Polymorphism at scale
(25 May 2020) Event sourcing and RavenDB
(07 Apr 2020) Managing Data in Distributed Environment
(06 Apr 2020) Building a grown up database
(12 Mar 2020) Migrating from a Relational Database to RavenDB

Comments

20 Jun 2020
20:25 PM

Ernest

Hi Oren, thanks for this interesting webinar. I have a question on using subscriptions for managing the read side of such a system. Are there any recommendations and/or limitations for subscriptions? What if I have a system that needs to create relatively large number of subscriptions, each filtering on a different set of message types? What is the reasonable upper boundary of number of active subscriptions without affecting the system's performance?

21 Jun 2020
05:07 AM

Oren Eini

Ernest,

We have tested subscriptions with 1000+ active clients and pumping 100,000 documents per second (across all of them).

Subscriptions will also naturally divide themselves among the members of the cluster, so reduce load even further.

Comment preview

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