Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.
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TimeXtender
Score 9.0 out of 10
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TimeXtender was designed to be a holistic solution for data integration that empowers organizations to build data solutions 10x faster using metadata and low-code automation.
$1,600
per month
Pricing
Azure Data Factory
TimeXtender
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data Factory
TimeXtender
Free Trial
No
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
On-Demand pricing is pay as you go, month-to-month, with no commitment, at the "on-demand" price of $3.33/credit.
More Pricing Information
Community Pulse
Azure Data Factory
TimeXtender
Features
Azure Data Factory
TimeXtender
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
8.0
8 Ratings
3% below category average
TimeXtender
-
Ratings
Connect to traditional data sources
9.08 Ratings
00 Ratings
Connecto to Big Data and NoSQL
7.18 Ratings
00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
8.0
8 Ratings
1% below category average
TimeXtender
-
Ratings
Simple transformations
9.08 Ratings
00 Ratings
Complex transformations
7.08 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
7.2
8 Ratings
8% below category average
TimeXtender
-
Ratings
Data model creation
7.06 Ratings
00 Ratings
Metadata management
7.07 Ratings
00 Ratings
Business rules and workflow
7.08 Ratings
00 Ratings
Collaboration
7.97 Ratings
00 Ratings
Testing and debugging
6.08 Ratings
00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.
TimeXtender has worked really well with our customers who have different data sources using complex data types in large quantities requiring a DW-like solution that can consolidate all data sources at one-HUB. TimeXtender does this well, and provides automation capabilities, the ability to easily handle slowly changing dimensions, handing data lineage and data security very well. TimeXtender has the ability to be very customizable, allowing the HUB to grow as your business does. TimeXtender's customer support team is super helpful and will work with you throughout your implementation to make sure you reach success with the product. The ROI for timeXtender versus competing products (there aren't many that do what timeXtender does) shows the investment to be worthwhile for the majority of organizations in today's data-rich corporate world.
It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
We can use linked service in multiple pipeline/data load.
It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.
Product Marketing: As implementers and resellers of this technology, we loved it. But, convincing clients who had not previously heard of TX/Discovery Hub was more difficult than it could have been if the company had a larger marketing force behind it.
Relatively New to Market: it creates a learning curve for early implementers.
More information should be published on timeXtender's website about product lines, including testimonials.
So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.
We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue
The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.
For our clients, timeXtender was a much better solution. It offered a more cost-effective solution, easier integration, and better customer support for our complex client needs. The timeXtender team worked with us throughout the process to make sure we could create a success story that was repeatable for our clients, and they proved great partners.