We performed a comparison between BigQuery and Microsoft Azure Synapse Analytics based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Even non-coders can review the data in BigQuery."
"The product’s most valuable feature is its ability to manage the database on the cloud."
"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
"It has a well-structured suite of complimentary tools for data integration and so forth."
"The query tool is scalable and allows for petabytes of data."
"It's similar to a Hadoop cluster, except it's managed by Google."
"When integrating their system into the cloud-based solutions, we were able to increase their efficiency and overall productivity twice compared with their on-premises option."
"The interface is what I find particularly valuable."
"Fills the gap between big data and classic data warehouses."
"It is a fantastic product; we are satisfied with its features and performance."
"We have found that it is easy to develop and to do the analytics in the modules of data."
"The product is easy to use, and anybody can easily migrate to advanced DB."
"The best thing about it is that it has integration at multiple places. It can talk to more than 90 types of data sources, which is one good thing about it."
"The most valuable features are the flexibility and that it's easy to use as an end-user compared to AWS."
"Synapse Analytics' best features are notebooks, pipelines, and monitoring."
"The most valuable feature is the level of processing power, and being able to complete tasks in parallel."
"We'd like to see more local data residency."
"For greater flexibility and ease of use, it would be beneficial if BigQuery offered more third-party add-ons and connectors, particularly for databases that don't have built-in integration options."
"We'd like to have more integrations with other technologies."
"There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans."
"The initial setup could be improved making it easier to deploy."
"So our challenge in Yemen is convincing many people to go to cloud services."
"The main challenges are in the areas of performance and cost optimizations."
"It would be beneficial to integrate additional tools, particularly from a business intelligence perspective."
"Synapse Analytics' performance slows down if you don't get your distribution right because it gets queued and goes into a single node."
"While the solution is flexible, sometimes this works against the user."
"Its stability is an issue. They have been releasing a version every six months to one year, which means that there are many versions available, and clients are not up to speed on the latest one that they're offering. From a stability point of view, they could do better. They're still upgrading their Synapse Analytics workspace, and it is not that stable. Its scalability can also be better."
"The linked services can be improved. We can create dynamic linked services to access a lot of databases but only those of the same type. For example, I can use the same linked services to access 11 SQL databases. However, if I have 11 SQL databases and five Oracle databases, I need two dynamic linked services. I cannot do it with only one linked service. The UI also needs to be improved. When I have used Azure Synapse for programming with PySpark, Scala, or .NET, for example, the UI has been unstable. If I open two notebooks for programming, one notebook will queue the session of the other."
"It would be beneficial to take the top vendors and identify some kind of straightforward action to work with them. Instead of having to employ a separate vendor tool to be able to move this, it would be nice to be able to go through Microsoft."
"Microsoft Azure Synapse Analytics can improve by adding more flexibility to the reports. Having more visible structures based on the area, region and country would be beneficial."
"It could be beneficial to focus on integration with various data sources and similar enhancements."
"Microsoft Azure Synapse Analytics's overall integration within the Azure ecosystem could improve. The native Microsoft solution versus another solution, such as Databricks, there are areas where there could be some improvements."
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BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 86 reviews. BigQuery is rated 8.2, while Microsoft Azure Synapse Analytics is rated 7.8. The top reviewer of BigQuery writes "Expandable and easy to set up but needs more local data residency". On the other hand, the top reviewer of Microsoft Azure Synapse Analytics writes "No competitors provide the entire solution to one place ". BigQuery is most compared with Snowflake, Teradata, Oracle Autonomous Data Warehouse, Vertica and VMware Tanzu Data Services, whereas Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Snowflake, Oracle Autonomous Data Warehouse and Teradata. See our BigQuery vs. Microsoft Azure Synapse Analytics report.
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