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Azure Synapse vs Power BI: What are the differences?

Azure Synapse and Power BI are both powerful Microsoft tools that offer analytics and business intelligence capabilities. Here are the key differences between them.

  1. Scalability and Data Storage: Azure Synapse is primarily designed for large-scale enterprise data warehousing and analytics. It can handle massive amounts of structured and unstructured data and provides limitless scaling capabilities. On the other hand, Power BI is more focused on data visualization and reporting, and therefore, it has limited capabilities in storing and processing large volumes of data.

  2. Data Integration and ETL: Azure Synapse offers comprehensive data integration and Extract, Transform, Load (ETL) capabilities. It provides tools like Azure Data Factory and Azure Databricks for data ingestion, transformation, and orchestration, and supports a wide range of data sources and connectors. Power BI, although it offers some data transformation capabilities, is more commonly used for data visualization and relies on external tools like Azure Data Factory for ETL processes.

  3. Real-time Analytics: Azure Synapse enables real-time analytics through its integration with Azure Stream Analytics and Azure Event Hubs. It can process and analyze streaming data in real-time, providing valuable insights for immediate decision-making. On the other hand, Power BI is more suited for batch processing and analyzing historical data rather than real-time streaming data.

  4. Machine Learning and AI Integration: Azure Synapse offers built-in integration with Azure Machine Learning and other AI services, allowing users to easily incorporate machine learning models and advanced analytics into their data workflows. Power BI, while it supports the consumption and visualization of machine learning models, lacks the robust integration capabilities of Azure Synapse.

  5. Collaboration and Sharing: Power BI is well-known for its collaboration and sharing capabilities, allowing users to create interactive reports and dashboards and easily share them with others within or outside the organization. Azure Synapse, on the other hand, is more focused on data analytics and lacks the collaborative features provided by Power BI.

  6. Cost and Pricing Model: Power BI offers a cost-effective pricing model based on the number of users and their access levels. It is suitable for small to medium-sized organizations with less complex data analysis requirements. Azure Synapse, on the other hand, has a more complex pricing model based on data storage, processing, and data movement, making it more suitable for large enterprises with extensive data analytics needs.

In summary, Azure Synapse is designed for large-scale data warehousing, ETL, real-time analytics, and machine learning integration, while Power BI is more focused on data visualization, collaboration, and sharing.

Decisions about Azure Synapse and Power BI
Vojtech Kopal
Head of Data at Mews Systems · | 3 upvotes · 297.5K views

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

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Pros of Azure Synapse
Pros of Power BI
  • 4
    ETL
  • 3
    Security
  • 2
    Serverless
  • 1
    Doesn't support cross database query
  • 17
    Cross-filtering
  • 2
    Powerful Calculation Engine
  • 2
    Access from anywhere
  • 2
    Intuitive and complete internal ETL
  • 2
    Database visualisation
  • 1
    Azure Based Service

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Cons of Azure Synapse
Cons of Power BI
  • 1
    Dictionary Size Limitation - CCI
  • 1
    Concurrency
    Be the first to leave a con

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    What is Azure Synapse?

    It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

    What is Power BI?

    It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

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    What are some alternatives to Azure Synapse and Power BI?
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    Google BigQuery
    Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
    Amazon Redshift
    It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
    Tableau
    Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
    Snowflake
    Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
    See all alternatives