Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…
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Qlik Talend Cloud
Score 8.9 out of 10
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The Talend Integration Suite, from Talend, is a set of tools for data integration.
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Pricing
Azure Databricks
Qlik Talend Cloud
Editions & Modules
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No answers on this topic
Offerings
Pricing Offerings
Azure Databricks
Qlik Talend Cloud
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Azure Databricks
Qlik Talend Cloud
Features
Azure Databricks
Qlik Talend Cloud
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
7.4
4 Ratings
12% below category average
Qlik Talend Cloud
-
Ratings
Connect to Multiple Data Sources
6.14 Ratings
00 Ratings
Extend Existing Data Sources
7.94 Ratings
00 Ratings
Automatic Data Format Detection
7.54 Ratings
00 Ratings
MDM Integration
8.03 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
6.7
4 Ratings
23% below category average
Qlik Talend Cloud
-
Ratings
Visualization
6.04 Ratings
00 Ratings
Interactive Data Analysis
7.53 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.6
4 Ratings
5% above category average
Qlik Talend Cloud
-
Ratings
Interactive Data Cleaning and Enrichment
8.14 Ratings
00 Ratings
Data Transformations
9.04 Ratings
00 Ratings
Data Encryption
9.44 Ratings
00 Ratings
Built-in Processors
7.84 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
8.0
4 Ratings
5% below category average
Qlik Talend Cloud
-
Ratings
Multiple Model Development Languages and Tools
6.54 Ratings
00 Ratings
Automated Machine Learning
8.64 Ratings
00 Ratings
Single platform for multiple model development
8.44 Ratings
00 Ratings
Self-Service Model Delivery
8.44 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Azure Databricks
8.3
4 Ratings
2% below category average
Qlik Talend Cloud
-
Ratings
Flexible Model Publishing Options
8.04 Ratings
00 Ratings
Security, Governance, and Cost Controls
8.64 Ratings
00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Databricks
-
Ratings
Qlik Talend Cloud
9.5
10 Ratings
14% above category average
Connect to traditional data sources
00 Ratings
10.010 Ratings
Connecto to Big Data and NoSQL
00 Ratings
9.09 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Databricks
-
Ratings
Qlik Talend Cloud
9.0
10 Ratings
11% above category average
Simple transformations
00 Ratings
9.010 Ratings
Complex transformations
00 Ratings
9.010 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Databricks
-
Ratings
Qlik Talend Cloud
9.0
10 Ratings
14% above category average
Data model creation
00 Ratings
9.09 Ratings
Metadata management
00 Ratings
10.09 Ratings
Business rules and workflow
00 Ratings
8.08 Ratings
Collaboration
00 Ratings
9.09 Ratings
Testing and debugging
00 Ratings
9.010 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Centralised notebooks are out directly into production. This can lead to poorly engineered code. It is very good for fast queries and our data team are always able to provide what we ask for. It is a big cost to our business so it is important it runs efficiently and returns on our investment.
This tool fits all kinds of organizations and helps to integrate data between many applications. We can use this tool as data integration is a key feature for all organizations. It is also available in the cloud, which makes the integration more seamless. The firm can opt for the required tools when there are no data integration needs.
Talend Data Integration allows us to quickly build data integrations without a tremendous amount of custom coding (some Java and JavaScript knowledge is still required).
I like the UI and it's very intuitive. Jobs are visual, allowing the team members to see the flow of the data, without having to read through the Java code that is generated.
The developers are able to switch between Python and SQL in the Notebook which allows the collaboration of SQL analyst and Data scientist. The integration of Mosaic AI allows users to write complex codes in natural languages. Unity catalog has centralized the security and governance features and simplified the process of maintaining it
We use Talend Data Integration day in and day out. It is the best and easiest tool to jump on to and use. We can build a basic integration super-fast. We could build basic integrations as fast as within the hour. It is also easy to build transformations and use Java to perform some operations.
Good support, specially when it relates to PROD environment. The support team has access to the product development team. Things are internally escalated to development team if there is a bug encountered. This helps the customer to get quick fix or patch designed for problem exceptions. I have also seen support showing their willingness to help develop custom connector for a newly available cloud based big data solution
I have found Azure Databricks to be much better than Snowflake for handling bigger, diverse data types. Snowflake is much simpler and better for smaller warehousing. The real time processing is much better in Azure Databricks and we have much more language options. Snowflake is more expensive but simpler to use. Both are great for different needs.
In comparison with the other ETLs I used, Talend is more flexible than Data Services (where you cannot create complex commands). It is similar to Datastage speaking about commands and interfaces. It is more user-friendly than ODI, which has a metadata point of view on its own, while Talend is more classic. It has both on-prem and cloud approaches, while Matillion is only cloud-based.
It’s only been a positive RoI with Talend given we’ve interfaced large datasets between critical on-Prem and cloud-native apps to efficiently run our business operations.