Azure Synapse vs Google BigQuery

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Azure Synapse

85
204
+ 1
10
Google BigQuery

1.5K
1.3K
+ 1
149
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Google BigQuery vs Azure Synapse: What are the differences?

Google BigQuery: Analyze terabytes of data in seconds. 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.; Azure Synapse: Analytics service that brings together enterprise data warehousing and Big Data analytics. 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.

Google BigQuery can be classified as a tool in the "Big Data as a Service" category, while Azure Synapse is grouped under "Big Data Tools".

Some of the features offered by Google BigQuery are:

  • All behind the scenes- Your queries can execute asynchronously in the background, and can be polled for status.
  • Import data with ease- Bulk load your data using Google Cloud Storage or stream it in bursts of up to 1,000 rows per second.
  • Affordable big data- The first Terabyte of data processed each month is free.

On the other hand, Azure Synapse provides the following key features:

  • Complete T-SQL based analytics – Generally Available
  • Deeply integrated Apache Spark
  • Hybrid data integration
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Pros of Azure Synapse
Pros of Google BigQuery
  • 4
    ETL
  • 3
    Security
  • 2
    Serverless
  • 1
    Doesn't support cross database query
  • 28
    High Performance
  • 25
    Easy to use
  • 21
    Fully managed service
  • 19
    Cheap Pricing
  • 16
    Process hundreds of GB in seconds
  • 11
    Full table scans in seconds, no indexes needed
  • 11
    Big Data
  • 8
    Always on, no per-hour costs
  • 6
    Good combination with fluentd
  • 4
    Machine learning

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Cons of Azure Synapse
Cons of Google BigQuery
  • 1
    Dictionary Size Limitation - CCI
  • 1
    Concurrency
  • 1
    You can't unit test changes in BQ data

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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 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.

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What companies use Azure Synapse?
What companies use Google BigQuery?
See which teams inside your own company are using Azure Synapse or Google BigQuery.
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What tools integrate with Azure Synapse?
What tools integrate with Google BigQuery?

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What are some alternatives to Azure Synapse and Google BigQuery?
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.
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.
Metabase
It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.
See all alternatives