In today’s cutting-edge times, when the pace of accumulation of information keeps on expanding dramatically on a consistent basis, the importance of Big Data and Analytics is evident. The huge volume of data being generated in various sectors and businesses has been on an exponential rise like never before, due to which the IT businesses have started to observe persistent development and continuous innovations in the effort to effectively manage the growing data challenges. Numerous organizations, that are beginning their cloud venture, wind up considering which modern cloud data warehouse/data platform technology to go with.
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Overview of Azure Synapse Analytics
Microsoft Azure Synapse Analytics is a cloud-based PaaS (Platform-as-a-Service) offering from Microsoft and provides an end-to-end analytics solution that successfully brings together analytical services to merge big data analytics and enterprise data warehousing into a single unified platform. It gives us the option to query data on our own terms, using either Server-less or Dedicated resources, at scale. This, the unified platform combines the needs of Machine Learning, Data Engineering, and Business Intelligence without a need to keep up with separate tools and processes.
Along with all of the features of a Data Warehouse, Azure Synapse offers us:
- Data Pipelines & ETL: Develop and orchestrate data pipelines within Synapse with Synapse Integrate
- Data Analytics: Perform complex SQL queries for data analytics and Bigdata Analytics with Spark
- Choice of Programming Language: Python, Scala, SQL, Spark, & .NET
- Machine Learning & AI: Develop AI & ML models from the dataset
- Business intelligence: Build Interactive reports through visualization tools like PowerBI
Ingest and Perform Query on both Structured as well as Unstructured Data
Azure Synapse ingests various types of data, which includes, but not limited to relational (DW) data and non-relational (Data Lake) data, and it lets us explore it with T-SQL queries. Hence, Synapse brings all of the structured and unstructured data (CRM, LOB, Image, Social, Graph, IoT, etc.) under the same platform for simple access and analysis so that you don’t need to use various systems to analyze structured and unstructured data.
Azure Data Lake Storage Gen2
Azure Data Lake Storage Gen2 brings together Gen1 features (like file-level security and scaling) along with Azure Blob Storage features (like disaster recovery, tiered storage, and high availability).
Massively Parallel Processing (MPP)
Azure Synapse leverages the massively parallel processing, MPP database technology, which enables it to manage analytical workloads and aggregate/process large volumes of data efficiently and effectively. Unlike transactional databases, which store rows in a table as an object, MPP databases store each column as an object. MPP databases also distribute data across various nodes that operate in parallel to process different parts of queries. This database architecture helps speed up long-running and complex analytical processes.
On-Demand Server-less or Provisioned Processing Resources
Synapse gives us the flexibility to query massive data stores using either an on-demand server-less deployment (which scales automatically as needed) or provisioned resources. This allows companies to either pay for what they need when they need it, or they can have pre-provisioned processing and storage capabilities.
Security and Privacy
Synapse incorporates the latest security and privacy technologies such as dynamic data masking, real-time data masking, always-on encryption, Azure Active Directory authentication, single-sign-on authentication, Multi-factor Authentication, and Advanced threat detection. The platform also allows us to control access to sensitive data via column and row-level security.
Also, Azure has more compliance certifications than any other cloud service provider available. These compliance certifications allow the companies to adhere to the most strict government and industry compliance standards.
Comparison with other vendors
Microsoft claims that Analytics in Azure Synapse Analytics is up to 380 percent faster and costs up to 49 percent less than other cloud providers. Azure Synapse offers a more concise and predictive pricing structure. Users can choose between on-demand pricing or pre-purchase data storage to earn a discount.
Azure outperforms Snowflake in both the medium and large enterprise TCO (Total Cost of Ownership) comparisons. Implementing an end-to-end analytics solution in Azure costs up to 59 % less compared to Snowflake.
Azure Synapse Analytics vs. AWS Redshift:
Azure outperforms AWS in both the medium and large enterprise TCO (Total Cost of Ownership comparisons. Implementing an end-to-end analytics solution in Azure costs up to 13 % less compared to AWS
Azure Synapse Analytics Vs. Google BigQuery
Azure outperforms Google in both the medium and large enterprise TCO (Total Cost of Ownership) comparisons. Implementing an end-to-end analytics solution in Azure costs up to 49 % less compared to Google.