Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.
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Apache Pulsar
Score 9.2 out of 10
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Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now an Apache Software Foundation project. It is free and open source, available under the Apache License, version 2.0.
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OpenAir PSA
Score 5.5 out of 10
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NetSuite OpenAir is a cloud-based Professional Service Automation (PSA) product which includes capabilities around project management, resource management, project accounting, etc.
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Pricing
Apache Kafka
Apache Pulsar
OpenAir PSA
Editions & Modules
No answers on this topic
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache Kafka
Apache Pulsar
OpenAir PSA
Free Trial
No
No
No
Free/Freemium Version
No
Yes
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Apache Kafka
Apache Pulsar
OpenAir PSA
Features
Apache Kafka
Apache Pulsar
OpenAir PSA
Project Management
Comparison of Project Management features of Product A and Product B
Apache Kafka
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Ratings
Apache Pulsar
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Ratings
OpenAir PSA
7.3
15 Ratings
6% below category average
Task Management
00 Ratings
00 Ratings
8.015 Ratings
Resource Management
00 Ratings
00 Ratings
7.515 Ratings
Gantt Charts
00 Ratings
00 Ratings
8.09 Ratings
Scheduling
00 Ratings
00 Ratings
6.012 Ratings
Workflow Automation
00 Ratings
00 Ratings
6.09 Ratings
Team Collaboration
00 Ratings
00 Ratings
8.012 Ratings
Support for Agile Methodology
00 Ratings
00 Ratings
6.07 Ratings
Support for Waterfall Methodology
00 Ratings
00 Ratings
7.08 Ratings
Document Management
00 Ratings
00 Ratings
8.56 Ratings
Email integration
00 Ratings
00 Ratings
7.09 Ratings
Mobile Access
00 Ratings
00 Ratings
7.512 Ratings
Timesheet Tracking
00 Ratings
00 Ratings
7.014 Ratings
Change request and Case Management
00 Ratings
00 Ratings
8.010 Ratings
Budget and Expense Management
00 Ratings
00 Ratings
7.514 Ratings
Professional Services Automation
Comparison of Professional Services Automation features of Product A and Product B
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
This product is well suited for an organization that is focused on client services, project delivery, time tracking, expense reporting, and revenue recognition. From a pure project management perspective, this product is not as feature rich as say Microsoft Project Server. For organizations that are looking for detailed complex project plan and resource management (along with resource leveling, etc.), this is probably not the best suited product
Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
Netsuite OpenAir PSA is highly configurable and has a large ecosystem of assets to work with.
Tasks are easily designed to automate processes in your business workflow.
OpenAir is designed in such a way that it can communicate and receive information from external systems without having to re-engineer your systems to make them work if you are following standard business practice.
Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
Learning curve around creation of broker and topics could be simplified
Compared to QuickArrow, setting up reports to reflect the data accurately seemed to require a bit more consultant time and collaboration. Getting the numbers correct is essential, so budget extra time for this iniative. We also learned that certain calculations can not be displayed in the executive dashboards. Ask these questions upfront to ensure your dashboards are complete for your needs (again, working backwards in the preparation stages).
Compared to QuickArrow, NetSuite OpenAir PSA falls short in the resource management capabilities. UI, flexibility, and scheduling options all could be improved. This is on their roadmap, timeline yet to be defined. Scheduling is vitally important to our company and this is THE area where we feel is the applications weakest. However, the application does provide everything critical to scheduling and provided the elements we needed in order to be successful. We altered our scheduling process accordingly.
During our System Administration 3 day online training, when a question was asked about detailed functionality, sometimes the trainer would share..."Yes, OpenAir has a configuration for that. Just inquire with your consultant and they can flip that flag in your instance." The responsibility for obtaining these special application configurations was placed on the System Admin [in training] to ask and to take notes. If your company needs the application to work a certain way, speak up and ask your OA consultant. There seems to be MANY flags that can be flipped in the background to allow for the system to meet your needs. My complaint is that these are not published, rather made available if one inquires.
OpenAir is able to generate invoices directly and we strongly encourage using this feature to keep everything housed under one application. However, this did not work for our organization and we leveraged a financial integration. A bit of a pioneer integrating with Softrax -- the integration works well, however is quite fragile. We do receive appropriate support when needed, but would prefer the integration to be a bit more stable. We recommend integrating with their stated supported financial systems, as staying the course will likely net a more stable integration.
It all depends. We are still looking at moving our consultants to Oracle PAC, in order to get our financial systems in line (we use Oracle Financials currently). We are feeling a lot of pain with integration and segmented systems.
Ultimately,it depends on how much pain is felt there. OpenAir has given us a path to follow on from QuickArrow. I foresee either moving onto Oracle PAC by end of calendar, or staying on OpenAir.
OpenAir to Oracle integration is not easy. From a reporting and process perspective, there’s been pain from being in different systems
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
In this day and age I should not have to read a manual to understand a product. It should be intuitive to administrate and perform basic tasks. It feels like a ton of intelligence was poured into making OpenAir feature rich but no where near as much attention was given to the user experience.
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
As an admin, I've had more contact with OA support than most. I've found their response to tickets typically timely and helpful, however many of the responses to tickets are "we will file an enhancement request" and then I never hear about it again. So not terrible, but not a very fulfilling experience.
Very knowledgeable and able to articulate how other customers configured the solution to meet their needs as well as the best practices they recommended.
We did a 3 day online remote course back in April. NetSuite prefers training to occur before migration. We went over the functionality of tool and three months later we migrated. Personally, I didn’t find it that beneficial. Certain parts of it were beneficial as they applied to me – talked a lot about invoicing capabilities that didn’t apply to me. They also have knowledge base / e-learning assets, but I haven’t referred to them
It went fine. Everything came over the way we wanted. In addition to migrating the current projects we wanted to migrate historical data – did that seamlessly. The finished product looked pretty good – just needed to tweak – and they helped us with that
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
OpenAir accurately reflects changes in real-time as well as lends itself to see where a draw is at, when payment is expected and what percentage of the contract has been billed or approved to date. This helps with project billing and tracking as well as cash flow. Quickbooks lacks the ability to show progress draws, approved changes, and pending changes on a given project where OpenAir excels.
Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
Positive: it's scalable so we can develop small and scale for real-world scenarios
Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.