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Azure Synapse vs Power BI Embedded: What are the differences?
# Comparison between Azure Synapse and Power BI Embedded
<Write Introduction here>
1. **Data Integration and Analysis Capabilities**: Azure Synapse is a comprehensive analytics service that enables integration, management, and analysis of data across the organization, including structured and unstructured data. On the other hand, Power BI Embedded is a platform-as-a-service offering that allows developers to embed Power BI reports and dashboards into custom applications.
2. **Scalability and Architecture**: Azure Synapse is designed for large-scale data processing and analytics, providing unlimited scalability to handle massive volumes of data. Power BI Embedded, on the other hand, is focused on embedding visual analytics within applications to provide interactive data insights to end-users.
3. **Data Processing and Transformation**: Azure Synapse offers powerful data processing and transformation capabilities with integrated Apache Spark and SQL engines for advanced analytics. Power BI Embedded, on the other hand, leverages the capabilities of Power BI Desktop and Power Query for data modeling and preparation.
4. **Cost Structure**: Azure Synapse follows a pay-as-you-go pricing model based on usage and data processing capacity, allowing organizations to scale resources based on requirements. Power BI Embedded, on the other hand, offers a capacity-based pricing model where organizations pay for the number of renders and API calls made by their applications.
5. **Deployment and Management**: Azure Synapse provides a unified workspace for data engineers, data scientists, and analysts to collaborate on data projects, with integrated security and governance features. Power BI Embedded focuses on easy deployment of interactive reports and dashboards within applications, with specific APIs for integration and customization.
6. **Target Audience and Use Cases**: Azure Synapse is geared towards organizations looking for an end-to-end analytics platform to unify data integration, data warehousing, and big data analytics. Power BI Embedded is ideal for developers seeking to enhance their applications with interactive visualizations and insights powered by Power BI.
In Summary, Azure Synapse and Power BI Embedded differ in terms of their data integration capabilities, scalability, data processing and transformation features, cost structure, deployment options, and target audience.
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Learn MorePros of Azure Synapse
Pros of Power BI Embedded
Pros of Azure Synapse
- ETL4
- Security3
- Serverless2
- Doesn't support cross database query1
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Cons of Azure Synapse
Cons of Power BI Embedded
Cons of Azure Synapse
- Dictionary Size Limitation - CCI1
- Concurrency1
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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 Embedded?
Quickly and easily provide customer-facing reports, dashboards, and analytics in your own applications by using and branding it as your own. Reduce developer resources by automating the monitoring, management, and deployment of analytics, while getting full control of Power BI features and intelligent analytics.
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What companies use Azure Synapse?
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What companies use Azure Synapse?
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What tools integrate with Azure Synapse?
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What are some alternatives to Azure Synapse and Power BI Embedded?
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.