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Qlik Replicate vs Teradata comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 12, 2025

Review summaries and opinions

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

ROI

Sentiment score
8.0
Qlik Replicate automates reporting, saves time, reduces database usage, minimizes costs, and improves efficiency compared to AWS services.
Sentiment score
8.1
Teradata boosts analytics speed over 100%, enhancing customer service and satisfaction, with high ROI and user approval.
I conducted a cost comparison with the AWS service provider, and this option is much cheaper than the Kinesis service offered by AWS.
 

Customer Service

Sentiment score
5.7
Users find Qlik Replicate support slow and inefficient, preferring quicker resolutions and direct contact with representatives, especially for AutoML issues.
Sentiment score
7.1
Teradata's customer service is praised for expertise but criticized for delays, with ratings ranging from 6 to 10 out of 10.
Even priority tickets, which should be resolved in minutes, can take days.
The technical support from Teradata is quite advanced.
Customer support is very good, rated eight out of ten under our essential agreement.
 

Scalability Issues

Sentiment score
7.1
Qlik Replicate is scalable and adaptable, especially in cloud environments, but may require memory adjustments for optimal performance.
Sentiment score
7.4
Teradata is praised for its scalability, speed, and flexibility, despite some complexity and cost challenges in cloud environments.
This expansion can occur without incurring downtime or taking systems offline.
Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU.
 

Stability Issues

Sentiment score
8.5
Qlik Replicate is highly stable and reliable, efficiently handling large volumes, with seamless recovery despite minor API concerns.
Sentiment score
8.4
Teradata excels in stability with minimal downtime, robust architecture, 99.9% uptime, and reliable performance, despite minor large dataset issues.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
 

Room For Improvement

Qlik Replicate needs better UI, error clarity, support, integration, pricing transparency, performance, and marketing to compete effectively.
Teradata users seek better transaction processing, enhanced scalability, modern interface, cloud focus, advanced analytics, and improved support and documentation.
It is a core-based licensing, which, especially in the banking industry, results in the system capacity being utilized up to a maximum of 60%.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
 

Setup Cost

Qlik Replicate's pricing is high and less flexible than competitors, suiting larger companies with extensive replication needs.
Teradata's high cost is justified by its superior performance, competitive total ownership costs, and flexible pricing models.
Licensing is calculated based on the machine's total capacity rather than actual usage.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
 

Valuable Features

Qlik Replicate offers real-time data capture, easy replication, and seamless integration for efficient data management and real-time analytics.
Teradata offers efficient, scalable data management with fast query performance, robust security, automation, and cloud flexibility for businesses.
Data retrieved from the system can be pushed to multiple places, supporting various divisions such as marketing, loans, and others.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
 

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
Teradata
Ranking in Data Integration
17th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
76
Ranking in other categories
Customer Experience Management (6th), Backup and Recovery (20th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)
 

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 Teradata is 1.0%, up from 0.4% 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.
SurjitChoudhury - PeerSpot reviewer
Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities
We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.
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Comparison Review

it_user232068 - PeerSpot reviewer
Aug 5, 2015
Netezza vs. Teradata
Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…
 

Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
12%
Insurance Company
10%
Manufacturing Company
9%
Financial Services Firm
26%
Computer Software Company
11%
Manufacturing Company
7%
Healthcare Company
7%
 

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...
Comparing Teradata and Oracle Database, which product do you think is better and why?
I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...
Which companies use Teradata and who is it most suitable for?
Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...
Is Teradata a difficult solution to work with?
Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...
 

Comparisons

 

Also Known As

Replicate, Qlik Replicate
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture
 

Overview

 

Sample Customers

American Cancer Society, Fanzz, SM Retail, Smart Modular, Tangerine Bank, Wellcare
Netflix
Find out what your peers are saying about Qlik Replicate vs. Teradata and other solutions. Updated: April 2025.
848,253 professionals have used our research since 2012.