Try our new research platform with insights from 80,000+ expert users

Qlik Replicate vs StreamSets comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Qlik Replicate
Ranking in Data Integration
16th
Average Rating
8.2
Reviews Sentiment
8.4
Number of Reviews
15
Ranking in other categories
No ranking in other categories
StreamSets
Ranking in Data Integration
9th
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
24
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Qlik Replicate is 3.4%, up from 3.2% compared to the previous year. The mindshare of StreamSets is 1.7%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

KrishnaBaddam - PeerSpot reviewer
Lightweight tool, ensures that data is replicated across different systems and simplify complex tasks such as defining relationships
Qlik Compose is something that will automate user's overall data modernization. Here data modernization includes data modeling, ETL jobs, etc. But the advantage is users can automate the overall process of data engineering and data modeling through Qlik Compose. I think that's useful when users are able to manage 60% of the workload automated. That will be very useful. That's fantastic. Replicate does not have a great AI capability. AI capabilities are present in Qlik Sense. Qlik Replicate is a very light tool. It is only meant to capture data from the log files, get the data, and transfer it, read that table structure, create the table structure, and transfer the data whenever there is a change. So, it basically integrates with the kernel of the operating system. The way it works is that these replicate tools will integrate with the kernel of the operating system, and they will access the redo log files of the database. The redo log should have access to all the files of the structure of the schema, too. So, using that technique, they redo all the data structures, create a similar structure, and replicate the structure in the target schema, table, and database. After that is done, it will start tracing the instances that are happening. For example, if data is inserted into the table, then an insert is fired on the statement on the table. So, that particular insert is captured. And based on that insert statement, it will pull the SQL query and say, "Okay, there is an insert. I need to get that data." It will get the data from the redo log itself rather than going to a database. Then, it will just pass that transaction into the target system, where it will just insert the data. And this happens instantaneously, within a microsecond. So, if there is an insert, an update, or a delete, everything is transferred immediately. It is picked from the redo log because it comes to the redo log, and then the redo log sends it to Qlik Replicate and Replicate to the target system on which Replicate is installed.
Reyansh Kumar - PeerSpot reviewer
We no longer need to hire highly skilled data engineers to create and monitor data pipelines
The things I like about StreamSets are its * overall user interface * efficiency * product features, which are all good. Also, the scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy. You just need to configure the data sources, the paths and their configurations, and you are ready to go. It is very efficient and very easy to use for ETL pipelines. It is a GUI-based interface in which you can easily create or design your own data pipelines with just a few clicks. As for moving data into modern analytics systems, we are using it with Microsoft Power BI, AWS, and some on-premises solutions, and it is very easy to get data from StreamSets into them. No hardcore coding or special technical expertise is required. It is also a no-code platform in which you can configure your data sources and data output for easy configuration of your data pipeline. This is a very important aspect because if a tool requires code development, we need to hire software developers to get the task done. By using StreamSets, it can be done with a few clicks.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"It is only meant to capture data from the log files, get the data, and transfer it, read that table structure, create the table structure, and transfer the data whenever there is a change."
"Qlik Replicate stands out with its cutting-edge technology and its ability to handle diverse data management tasks. This powerful tool allows us to efficiently and swiftly load data into various data stores or destinations, while also enabling easy distribution across different endpoints. A notable feature is its capability to reload data from multiple sources by creating multiple tasks within a brief timeframe of fifteen to twenty minutes. This eliminates the need for manual intervention and ensures quick data loading from different tables."
"The most valuable features of Qlik Replicate are its CDC performance and trigger functions. CDC feature is important to the financial industry."
"Support has been great."
"A valuable feature of Qlik Replicate is that you do not need ETL. It's easy to use—you choose two systems and it automatically replicates them. Even if there is no CDC available, if you insert it and update it, and there is nothing to find out, then you can use Qlik Replicate. It's a good product."
"It's very user-friendly when it comes to settings and configuration. It also offers very detailed logging about warnings and errors."
"A pretty good series of connectors is one of the best features of Qlik Replicate."
"Great with replicating and updating records."
"StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."
"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."
"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source systems."
"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."
"I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks."
"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."
"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."
"The ability to have a good bifurcation rate and fewer mistakes is valuable."
 

Cons

"We'd like better connectivity."
"We would like to see more details in messages about errors with the system."
"It's not possible to replicate the QVC files in data analytics."
"Some features can also be overly dependent on each other. So, there is room for improvement."
"The disadvantage is people are not going for this license because it is not marketed properly."
"Support-wise, this solution is in need of improvement."
"The solution's flexibility to work with APIs should also be improved since it is very weak in working with APIs."
"It would be better if the solution’s pricing were more obvious."
"Using ETL pipelines is a bit complicated and requires some technical aid."
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"The data collector in StreamSets has to be designed properly. For example, a simple database configuration with MySQL DB requires the MySQL Connector to be installed."
"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."
"Visualization and monitoring need to be improved and refined."
"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."
"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."
 

Pricing and Cost Advice

"Unlike Azure, where you pay based on consumption, Qlik Replicate seems to charge per endpoint."
"Pricing for this solution is very reasonable."
"Qlik Replicate is mainly suited for large companies. However, it is too costly for small businesses. Its pricing is high."
"Overall, Qlik is an expensive solution. You need to pay for all additional features that you would like to use."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Qlik Replicate's pricing a nine out of ten."
"Qlik Replicate is not expensive, compared to GoldenGate."
"Its pricing is pretty much up to the mark. For smaller enterprises, it could be a big price to pay at the initial stage of operations, but the moment you have the Seed B or Seed C funding and you want to scale up your operations and aren't much worried about the funds, at that point in time, you would need a solution that could be scaled."
"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."
"It has a CPU core-based licensing, which works for us and is quite good."
"StreamSets is an expensive solution."
"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."
"There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."
"The licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."
"I believe the pricing is not equitable."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
816,406 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
13%
Manufacturing Company
12%
Insurance Company
8%
Financial Services Firm
17%
Computer Software Company
13%
Manufacturing Company
8%
Insurance Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Qlik Replicate?
The main valuable feature is its real-time change data capture (CDC) capabilities, which process data with minimal latency. There is not much delay. It also performs well with batch-wise data appli...
What needs improvement with Qlik Replicate?
The disadvantage is, I think, people are not going for this license because it is not marketed properly. Qlik was not promoting it because Talend was acquired at the same time. So Talend has become...
What is your primary use case for Qlik Replicate?
Qlik Compose is basically an integration tool, which has been acquired by Qlik from an Israeli IT company. So that Qlik can become leaders or can jump into the integration space. So, there are two ...
What do you like most about StreamSets?
The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...
What needs improvement with StreamSets?
We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which ...
What is your primary use case for StreamSets?
StreamSets is used for data transformation rather than ETL processes. It focuses on transforming data directly from sources without handling the extraction part of the process. The transformed data...
 

Also Known As

Replicate, Qlik Replicate
No data available
 

Learn More

Video not available
 

Overview

 

Sample Customers

American Cancer Society, Fanzz, SM Retail, Smart Modular, Tangerine Bank, Wellcare
Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
Find out what your peers are saying about Qlik Replicate vs. StreamSets and other solutions. Updated: November 2024.
816,406 professionals have used our research since 2012.