Informatica Cloud Data Integration, for Cloud ETL and ELT, enables users to ingest, integrate and cleanse data within Informatica's cloud-native ETL and ELT solution. Users can link source and target data with thousands of connectors that recognize metadata, to make it easier to run complex integrations.
N/A
RabbitMQ
Score 9.0 out of 10
N/A
RabbitMQ, an open source message broker, is part of Pivotal Software, a VMware company acquired in 2019, and supports message queue, multiple messaging protocols, and more.
RabbitMQ is available open source, however VMware also offers a range of commercial services for RabbitMQ; these are available as part of the Pivotal App Suite.
N/A
Pricing
Informatica Cloud Data Integration
RabbitMQ
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Informatica Cloud Data Integration
RabbitMQ
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
Informatica Cloud Data Integration
RabbitMQ
Features
Informatica Cloud Data Integration
RabbitMQ
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Informatica Cloud Data Integration
10.0
2 Ratings
19% above category average
RabbitMQ
-
Ratings
Connect to traditional data sources
10.02 Ratings
00 Ratings
Connecto to Big Data and NoSQL
10.02 Ratings
00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Informatica Cloud Data Integration
8.5
2 Ratings
5% above category average
RabbitMQ
-
Ratings
Simple transformations
10.02 Ratings
00 Ratings
Complex transformations
7.02 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Informatica Cloud Data Integration
8.3
2 Ratings
6% above category average
RabbitMQ
-
Ratings
Data model creation
9.01 Ratings
00 Ratings
Metadata management
9.01 Ratings
00 Ratings
Business rules and workflow
9.01 Ratings
00 Ratings
Collaboration
7.02 Ratings
00 Ratings
Testing and debugging
7.02 Ratings
00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
We use it a lot for importing data. We transform the incoming data to match the formatting of our CRM. We also match on existing records to avoid creating duplicates. Informatica handles all of this exceptionally well. Our users are system administrators. The tool is not well-suited for users who do not have a technical background
It is highly recommended that if you have microservices architecture and if you want to solve 2 phase commit issue, you should use RabbitMQ for communication between microservices. It is a quick and reliable mode of communication between microservices. It is also helpful if you want to implement a job and worker mechanism. You can push the jobs into RabbitMQ and that will be sent to the consumer. It is highly reliable so you won't miss any jobs and you can also implement a retry of jobs with the dead letter queue feature. It will be also helpful in time-consuming API. You can put time-consuming items into a queue so they will be processed later and your API will be quick.
What RabbitMQ does well is what it's advertised to do. It is good at providing lots of high volume, high availability queue. We've seen it handle upwards of 10 million messages in its queues, spread out over 200 queues before its publish/consume rates dipped. So yeah, it can definitely handle a lot of messages and a lot of queues. Depending on the size of the machine RabbitMQ is running on, I'm sure it can handle more.
Decent number of plugins! Want a plugin that gives you an interface to view all the queues and see their publish/consume rates? Yes, there's one for that. Want a plugin to "shovel" messages from one queue to another in an emergency? Check. Want a plugin that does extra logging for all the messages received? Got you covered!
Lots of configuration possibilities. We've tuned over 100 settings over the past year to get the performance and reliability just right. This could be a downside though--it's pretty confusing and some settings were hard to understand.
It breaks communication if we don't acknowledge early. In some cases our work items are time consuming that will take a time and in that scenario we are getting errors that RabbitMQ broke the channel. It will be good if RabbitMQ provides two acknowledgements, one is for that it has been received at client side and second ack is client is completed the processing part.
RabbitMQ is very easy to configure for all supported languages (Python, Java, etc.). I have personally used it on Raspberry Pi devices via a Flask Python API as well as in Java applications. I was able to learn it quickly and now have full mastery of it. I highly recommend it for any IoT project.
I gave it a 10 but we do not have a support contract with any company for RabbitMQ so there is no official support in that regard. However, there is a community and questions asked on StackOverflow or any other major question and answer site will usually get a response.
RabbitMQ has a few advantages over Azure Service Bus 1) RMQ handles substantially larger files - ASB tops out at 100MB, we use RabbitMQfor files over 200MB 2) RabbitMQ can be easily setup on prem - Azure Service Bus is cloud only 3) RabbitMQ exchanges are easier to configure over ASB subscriptions ASB has a few advantages too 1) Cloud based - just a few mouse clicks and you're up and running
Positive: we don't need to keep way too many backend machines around to deal with bursts because RabbitMQ can absorb and buffer bursts long enough to let an understaffed set of backend services to catch up on processing. Hard to put a number to it but we probably save $5k a month having fewer machines around.
Negative: we've got many angry customers due to queues suddenly disappearing and dropping our messages when we try to publish to them afterward. Ideally, RabbitMQ should warn the user when queues expire due to inactivity but it doesn't, and due to our own bugs we've lost a lot of customer data as a result.
Positive: makes decoupling the web and API services from the deeper backend services easier by providing queues as an interface. This allowed us to split up our teams and have them develop independently of each other, speeding up software development.