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Qlik Replicate vs StreamSets comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

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

Categories and Ranking

Qlik Replicate
Ranking in Data Integration
13th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
17
Ranking in other categories
No ranking in other categories
StreamSets
Ranking in Data Integration
15th
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
21
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of Qlik Replicate is 3.1%, up from 2.9% compared to the previous year. The mindshare of StreamSets is 1.6%, 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.
Nantabo Jackie - PeerSpot reviewer
Simplified pipelines and helped us break down data silos within our organization
The design experience when implementing batch streaming or ECL pipelines is very easy and straightforward. When we initially attempted to integrate StreamSets with Kafka, it was somewhat challenging until we consulted the documentation, after which it became straightforward. We use StreamSets to move data into modern analytics platforms. Moving the data into modern analytics platforms is still complex. It requires a lot of understanding of logic. StreamSets enables us to build data pipelines without knowing how to code. StreamSets' ability to build data pipelines without requiring us to know complex programming is very important, as it allows us to focus on our projects without spending time writing code. StreamSets' Transformer for Snowflake is simple to use for designing both simple and complex transformation logic. StreamSets' Transformer for Snowflake is extremely important to me as it helps me to connect external data sources and keep my internal workflow organized. Transformer for Snowflake's functionality is a perfect ten out of ten. It is important and cost-effective that Transformer for Snowflake is a serverless engine embedded within the platform, as without this feature, it would be very expensive. This feature helps us to sell at lower budget costs, which would otherwise be at a high cost with other servers. StreamSets has helped improve our organization. StreamSets simplified pipelines for our organization. It is easier to complete a project when we know where and how to start, and working with the team remotely makes it more efficient. This helps us to save time and be more organized when creating data pipelines. Being a structured company that produces reliable resources for our application benefits both our clients and contacts. StreamSets' built-in data drift resilience plays a part in our ETL operations. With prior knowledge, the built-in data drift resilience is very effective, but it can be challenging to implement without the preexisting knowledge. The built-in data drift resilience reduced the time it takes us to fix data drift breakages by 45 percent. StreamSets helped us break down data silos within our organization. The use of StreamSets to break down data silos enabled us to be confident in the services and products we provide, as well as the real-time streaming we offer. This has had a positive impact on our business, as it allowed us to accurately determine the analytics we need to present to stakeholders, clients, and our sources while ensuring that the process is secure and transparent. StreamSets saved us time because anyone can use StreamSets not just developers. We can save around 40 percent of our time. StreamSets' reusable assets helped us reduce workload by around 25 percent. StreamSets saved us money by not having to hire developers with specialized skills. We saved around $2,000 US. StreamSets helped us scale our data operations. Since StreamSets makes it easy to scale our data operations, it enabled us to know exactly where to start at any time. We are aware of the timeline for completing the project, and depending on our familiarity with the software, we can come up with a solution quickly.

Quotes from Members

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

Pros

"The system is basically user-driven, mostly operating as a local platform."
"The most valuable features of Qlik Replicate are its CDC performance and trigger functions. CDC feature is important to the financial industry."
"Great with replicating and updating records."
"A pretty good series of connectors is one of the best features of Qlik Replicate."
"The cost is under control with this solution, unlike other services where it's not."
"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 applications."
"Low-priced reporting and analytics solution, with good scalability and stability. It has on-premises and cloud versions that are cohesive and can integrate well."
"From a technical perspective, this is an excellent product."
"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."
"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."
"StreamSets is the leader in the market."
"In StreamSets, everything is in one place."
"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 customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."
"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."
"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."
"The ability to have a good bifurcation rate and fewer mistakes is valuable."
 

Cons

"Support-wise, this solution is in need of improvement."
"I am not very comfortable with Qlik support as it often goes in loops. Even priority tickets, which should be resolved in minutes, can take days."
"The solution's flexibility to work with APIs should also be improved since it is very weak in working with APIs."
"When you remote into it the Qlik Replicate UI a lot of times it just freezes. We set up the EC2, to allow them to go to the server and click on the Replicate icon, it just opens up and just sits there. At that point, we have to go into the EC2 and then reboot the server. This should be fixed, it is frustrating."
"The disadvantage is people are not going for this license because it is not marketed properly."
"Some features on the graphical user interface are clunky."
"In the next release, I would like to see closer integration with data catalyst."
"We'd like better connectivity."
"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."
"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."
"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."
"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 was painful. Also, pipeline failures were common, and data drifting wasn't addressed, which made things worse. Licensing was another issue we encountered."
"One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infrastructure."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."
 

Pricing and Cost Advice

"Qlik Replicate is not expensive, compared to GoldenGate."
"Unlike Azure, where you pay based on consumption, Qlik Replicate seems to charge per endpoint."
"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 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."
"Pricing for this solution is very reasonable."
"The pricing is affordable for any business."
"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."
"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."
"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."
"StreamSets is an expensive solution."
"It has a CPU core-based licensing, which works for us and is quite good."
"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."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
11%
Insurance Company
10%
Manufacturing Company
10%
Financial Services Firm
14%
Computer Software Company
11%
Manufacturing Company
10%
Insurance Company
8%
 

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?
There is complexity involved in the licensing part of this system. It is a core-based licensing, which, especially in the banking industry, results in the system capacity being utilized up to a max...
What is your primary use case for Qlik Replicate?
An example involving the banking project I am currently working on is for a public sector bank in India. Primarily, they are using a database, and the ultra architecture is meant to take a backup o...
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
 

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: February 2025.
845,040 professionals have used our research since 2012.