Microsoft Azure Synapse Analytics and Google BigQuery compete in the cloud data warehousing category. Based on feature integration and scalability, Microsoft Azure Synapse Analytics may have the upper hand for enterprise users.
Features: Microsoft Azure Synapse Analytics is known for easy setup, seamless integration with Power BI, and scalability through its Massively Parallel Processing architecture. BigQuery stands out for its storage capabilities, performance speed, and seamless machine-learning integration.
Room for Improvement: Microsoft Azure Synapse Analytics could improve in pricing transparency, interface usability, and better integration with Active Directory. BigQuery's enhancements could include better handling of special characters during data migration, query caching, and more diverse data source integration options.
Ease of Deployment and Customer Service: Microsoft Azure Synapse Analytics offers flexibility with deployment options across public, private, and hybrid cloud environments, although tech support experiences vary. BigQuery is praised for its straightforward deployment in the public cloud, with generally positive experiences with Google's technical support.
Pricing and ROI: Microsoft Azure Synapse Analytics offers a flexible pricing structure but can lead to cost unpredictability, impacting smaller business adoption. However, it shows good ROI through reduced operational costs. BigQuery is reasonably priced, using a pay-as-you-go model based on data usage, but careful cost planning is necessary despite its competitive pricing for large data volumes.
I have been self-taught and I have been able to handle all my problems alone.
rating the customer support at ten points out of ten
Not monitoring data results often in a big impact on customer services and customer perception.
They are slow to respond and not very knowledgeable.
It is a 10 out of 10 in terms of scalability.
The scalability is definitely good because we are migrating to the cloud since the computers on the premises or the big database we need are no longer enough.
For the scalability of Microsoft Azure Synapse Analytics, I would rate it a 10 until you remain in the Azure Cloud scalability framework.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
I find the service stable as I have not encountered many issues.
Troubleshooting requires opening each pipeline individually, which is time-consuming.
BigQuery is already integrating Gemini AI into the data extraction process directly in order to reduce costs.
In general, if I know SQL and start playing around, it will start making sense.
Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth.
There is a need for better documentation, particularly for customized tasks with Microsoft Azure Synapse Analytics.
Being able to optimize the queries to data is critical. Otherwise, you could spend a fortune.
The price is perceived as expensive, rated at eight out of ten in terms of costliness.
I think the price of Microsoft Azure Synapse Analytics is very expensive, but that's not only for Microsoft Azure Synapse Analytics—it's for the cloud in general.
It is really fast because it can process millions of rows in just a matter of one or two seconds.
The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data.
BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes.
For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. ... You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.
Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.
Microsoft Azure Synapse Analytics is built with these 4 components:
Microsoft Azure Synapse Analytics Features
Microsoft Azure Synapse Analytics has many valuable key features, including:
Microsoft Azure Synapse Analytics Benefits
Some of the benefits of using Microsoft Azure Synapse Analytics include:
Reviews from Real Users
Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.
PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."
Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."
A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.