Likelihood to Recommend It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an
Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.
Read full review Denodo allows us to create and combine new views to create a virtual repository and APIs without a single line of code. It is excellent because it can present connectors with a view format for downstream consumers by flattening a JSON file. Reading or connecting to various sources and displaying a tabular view is an excellent feature. The product's technical data catalog is well-organized.
Read full review Pros Create data pipelines to connect with multiple data workspace(s) and external data Ability to connect with Azure Data Lake (sequentially) for data warehousing Being able to manage connections and create integration runtimes (for onPrem data capture) Read full review Database Agnostic: You can easily connect to different environments and mash up data sets. The "magic" of data virtualization: No data is created, so data is reported in near-real-time to end users. It's easy to use UI for developers. You just connect to a data source, create tables, and join them to other datasets. Read full review Cons It takes some time to setup a proper SQL Datawarehouse architecture. Without proper SSIS/automation scripts, this can be a very daunting task. It takes a lot of foresight when designing a Data Warehouse. If not properly designed, it can be very troublesome to use and/or modify later on. It takes a lot of effort to maintain. Businesses are continually changing. With that, a full time staff member or more will be required to maintain the SQL Data Warehouse. Read full review Caching - but I am sure it will be improved by now. There were times when we expected the cache to be refreshed but it was stale. Schema generation of endpoints from API response was sometimes incomplete as not all API calls returned all the fields. Will be good to have an ability to load the schema itself (XSD/JSON/Soap XML etc). Denodo exposed web services were in preliminary stage when we used; I'm sure it will be improved by now. Export/Import deployment, while it was helpful, there were unexpected issues without any errors during deployment. Issues were only identified during testing. Some views were not created properly and did not work. If it was working in the environment from where it was exported from, it should work in the environment where it is imported. Read full review Usability The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.
Read full review Denodo is very easy to use. It has a user-friendly drag and drop interface. I'm not a fan of the java platform it resides on.
Read full review Performance Denodo is a tool to rapidly mash data sources together and create meaningful datasets. It does have its downfalls though. When you create larger, more complex datasets, you will most likely need to cache your datasets, regardless of how proper your joins are set up. Since DV takes data from multiple environments, you are taxing the corporate network, so you need to be conscious of how much data you are sending through the network and truly understand how and when to join datasets due to this.
Read full review Support Rating Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.
Read full review Alternatives Considered When client is already having or using Azure then it’s wise to go with Synapse rather than using
Snowflake . We got a lot of help from Microsoft consultants and Microsoft partners while implementing our EDW via Synapse and support is easily available via Microsoft resources and blogs. I don’t see that with
Snowflake Read full review Denodo is simple and easy to use. Highly recommended unless you have huge volumes of data
Read full review Contract Terms and Pricing Model Basically, the billing is predictable, and this all about it.
Read full review Return on Investment We have had an improvement in our overall processing time Cost was much lower than most of its competitors Our reporting needs have grown and housing the data here has been great Read full review It is a huge advantage that we can connect to many different databases to provide data rapidly and accurately. It has proven to be a valuable environment for deploying data virtualization solutions, and its user community is active in finding and fixing issues. Read full review ScreenShots