Rivery Complete SaaS ELT & Workflow Orchestration

My main use case for Rivery  is classic ETL, bringing data from business data sources into a central data warehouse.

A quick specific example of a business data source I bring in is Salesforce , where I bring in opportunities, accounts, and other data. We then manipulate that data in order to create dashboards, reports, or automations.

The best features Rivery  offers include simplicity; it is a very simple tool that I can teach very quickly to my developers and analysts. I do not need classical data engineer skills in order to use it. It is also very friendly for analysts who can understand what is happening in their ETL pipelines and even do some work instead of data engineers.

The second point is flexibility, as I can use Rivery's classic SaaS built-in connectors, and we utilize a lot of custom connectors that are not built into the product, but we write them in a very simple way. We use Python, so we have the whole package from a very simple GUI mechanism into high-level coding if we need it.

Among the features I mentioned, I personally find myself using or appreciating the flexibility the most in my day-to-day work.

Rivery has positively impacted my organization by reducing the need for a big team of data engineers and speeding up the work when we need to connect to a new data source; this can happen really fast. I cannot provide specific numbers on how much time I have saved, but I can say that the team did not grow exponentially as the headcount in the whole company, which is a good sign.

Rivery can be improved by generally investing a bit more depth into the product, mainly in orchestration and specific features comparable to mature products. They also need to improve their logging and orchestration capabilities.

I have been using Rivery for around five to six years.

Rivery is stable.

Rivery handles increasing amounts of data or more complex workloads quite well, as we did not experience any issues with that.

The support is generally great, and while the user interface is acceptable, if I have an issue, it is a bit hard to understand what happened, so many times I need to reach out to support if I have issues; this is a bottleneck.

Customer support is great; they are answering really fast.

We did not use previous solutions; we are Rivery customers from day one.

I think we needed fewer employees and saved time, as I mentioned.

I found the pricing and licensing to be fair and competitive compared to other solutions I have seen.

Rivery is a great product; I recommend checking it out. I would rate Rivery as an eight out of ten because it is generally a great product, but it still needs some improvements.

Neutral

I have been using Rivery  to create and maintain data pipelines in configuration together with Snowflake , and it was very convenient.

I used Rivery  for creating a data application that performed system dynamic simulation, and this application was deployed in Snowflake . The application used Python programming language and SQL primarily. The task involved loading data from source to target, confronting the ETL process, and I used Rivery to build the data pipeline.

The process was highly automated on Rivery's side, so I created pipelines to clean up the data as well. The key aspect here is automation.

In my opinion, the most useful features Rivery offers are automated pipelines, data quality checks, and transformations. I would highlight automation again, as everything is built out of the box, and you don't need to spend a lot of time creating underlying code. You focus on logic and what exactly your application needs to do, and that is the essence.

The main benefit Rivery brought to my organization was the time we were able to save on development, and by using all these automation features provided by Rivery together with integration to Snowflake, we were able to solve problems. This was very useful and had the highest impact for our organization because we did not have dedicated data engineers or DevOps at that time.

As an end user of Rivery, I would like to see it be less commercial for users. To me, Rivery does not seem expensive, but it still feels commercial, and the problem is that there are many alternatives that can be built nowadays using Gen  AI. For example, agentic AI with open source tools can be used to build all configurations automatically for pipelines.

I think Rivery should be more integrated with modern AI tools such as agentic AI tools and specific protocols for MCPs. This would allow me to use Rivery out of the box from Claude and attach it as MCP for direct deployment.

I have been using Rivery for around six months.

I have not experienced issues with downtime or reliability, as Rivery was working smoothly.

I have not tried scaling up my workloads or projects with Rivery at all.

I have interacted with Rivery's support team, and it was very helpful. One of their specialists even contacted me on LinkedIn, so I really enjoyed this experience.

Negative

I have used a lot of different solutions for data integration. I am quite experienced in data operations, and I mostly used open source tools such as Hive  and HDFS to build ETL pipelines, and for transformations, I used Scala  applications.

By using Snowflake and Rivery, I was able to set up and complete project goals myself without the necessity to employ additional data engineers or DevOps, so I saved funds on paying for an additional position.

I do not remember how the pricing process was organized regarding the purchases, but I think we signed up for the smallest feasible plan at that time, which was about ten months or a year ago.

One more feature I appreciated was the use case repository of existing use cases, transformations, and examples of how data pipelines are built for social media marketing campaigns. I found them very useful, and I also changed and adapted some of these cases for the project I was working on at that time.

When I chose Rivery, the main criteria was integration with Snowflake because it was the main solution using Snowflake technology. It was mandatory to find something applicable, something simple, and something that could quickly solve all necessary requirements.

My advice would be to look for a specific use case which Rivery can help to solve quickly and consider opportunities to replace specific roles such as DevOps, DataOps, or data engineers by using Rivery. I would rate this review a 7 overall.

My main use case for Rivery  involves collecting data from different sources, and with Rivery , I am able to put them together and load the data directly in Snowflake .

The best features Rivery offers for me include the possibility to connect to different data sources, which is really interesting. Sometimes with other tools, there is a challenge in having connectors for specific sources, so this feature really makes my work easier.

Regarding my experience with the connectors, I did not have a lot of problems, and it was nice that I could also directly connect to sources that were NoSQL databases.

Rivery has positively impacted my organization because my colleagues who used it say that it really helps to do a part of the work that with other tools could be more challenging.

I think Rivery could be improved by having more analytical features inside. I do not know if in the latest updates there are some AI tools to use or something related to that.

Sometimes I wish for a small interface that can give an example of the data you are loading on the platform, which is an improvement needed for Rivery that I have not mentioned yet.

I have been using Rivery for a short time, mainly to do some exercises and little projects connecting Rivery to Snowflake .

The process of using Rivery has worked very smoothly for me, and I found the tool very easy to use, allowing me to gain a lot of insights. The tool is really useful and fast and easy to use.

The kind of work that became easier due to Rivery is the same as I already mentioned; the focus is on the ability to connect to different sources and to put all the data together.

Rivery is a really promising tool that could be developed in the future, as it could have a lot of utility for different companies.

My advice to others looking into using Rivery is that it is easy to use, so you do not need a lot of training to use it. I would recommend diving into the different features and looking for what is best. The documentation is easy to find.

I found this interview very smooth, and I think for my experience with Rivery, it is good enough.

I would rate Rivery overall as a nine out of ten.

I have been using Rivery  for two years.

My main use case for Rivery  is data ingestion and transformation workflows with Snowflake .

A quick, specific example of how I use Rivery with Snowflake  in my workflows is managing pipelines, monitoring data loads, and the performance for larger data sets.

The best features Rivery offers are the smooth integration with Snowflake, which does not require much manual setup, and it helped me get up and running quickly. It is easy to manage.

What stands out most to me about the integration with Snowflake and the ease of management is that it is easy to set up and it has a great user interface.

Rivery has positively impacted my organization by helping me streamline my data ingestion and transformation processes, especially in combination with Snowflake. Since I started using it, I have seen more reliable pipelines, faster time to data availability, and less manual effort needed to maintain integrations. It also improved visibility into data flows, which made troubleshooting and day-to-day operations easier for the whole team.

There is still room for advanced customizations and debugging. As an end-to-end solution for ETL with Snowflake, Rivery has proven to be reliable and efficient in my day-to-day work.

I have been working as a software tester for five years.

In my experience, Rivery is stable.

Rivery has scaled well for my needs so far. It has handled growing data volumes and additional pipelines without major issues, and we have not had to make significant changes to our setup as usage increased. Performance has remained stable, which made scaling relatively smooth.

I have not had to reach out to customer support, so I do not have any experience.

I did not previously use a different solution before Rivery.

I do not know if we purchased Rivery through AWS Marketplace  as it was not my job to set it up.

I have seen a return on investment from using Rivery. It saved my team time and really reduced manual work, so overall, it improved efficiency.

I do not know about the experience with pricing, setup cost, and licensing as it was not part of my job.

I do not know if we evaluated other options before choosing Rivery because it was not part of my job.

I do not have anything more to add about the features, automation, scheduling, or anything else that comes to mind.

I am not prepared with statistics for now regarding specific outcomes or metrics, such as time saved, reduction in errors, or other improvements I have seen since using Rivery.

I cannot tell if my company has a business relationship with this vendor other than being a customer.

I gave this review a rating of 8.