Cloud data simplified: a great all-in-one tool for all your data analytics needs
Our data warehouse was growing at a 1TB/year rate, and we needed a solution that would be both cheap and effective.
Previously we were …
Previously we were …
Starting at $4,700 per month 5000 Synapse Commit Units (SCUs)
View PricingOverview
What is Azure Synapse Analytics?
Azure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless…
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Pricing
Tier 1
$4,700
Cloud
per month 5,000 Synapse Commit Units (SCUs)
Tier 2
$9,200
Cloud
per month 10,000 Synapse Commit Units (SCUs)
Tier 3
$21,360
Cloud
per month 24,000 Synapse Commit Units (SCUs)
Entry-level set up fee?
- No setup fee
For the latest information on pricing, visithttps://azure.microsoft.com/en…
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Starting price (does not include set up fee)
- $4,700 per month 5000 Synapse Commit Units (SCUs)
Product Details
- About
- Tech Details
- FAQs
What is Azure Synapse Analytics?
Azure Synapse Analytics Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
Frequently Asked Questions
Azure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
Azure Synapse Analytics starts at $4700.
The most common users of Azure Synapse Analytics are from Enterprises (1,001+ employees).
Comparisons
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Reviews and Ratings
(51)Attribute Ratings
Reviews
(1-9 of 9)Companies can't remove reviews or game the system. Here's why
- Build, schedule and monitor complex data pipelines (Azure Data Factory component)
- Access your data lake using the familiar T-SQL syntax and TDS-enabled tools (SSMS, ADS, ...). This is especially useful for business people that are used to a specific workflow.
- Support a wide range of data transformation tools, from low-code (DataFlows) to full-code (Spark), all integrated in a single central orchestrator (Azure Data Factory-like)
- Provide all these services as a single very convenient package, without the need to know beforehand all the configuration behind
- There's no support for Synapse Serverless objects (e.g., views) in SSDT - the VCS-friendly approach to schema deployments from Microsoft. SSDT is available for almost all other SQL Server and Azure SQL products, including Synapse Dedicated SQL Pools.
- There are lots of ways to accomplish the same task, and it's not very clear which one is best suited for a given scenario other than trial and error. Also, some scenarios (e.g., efficient management of late arrivals) don't have a clear solution path.
- I think it would be cool to have a tighter integration of the product with the Azure Data Studio client, not only for connecting to SQL Serverless or Dedicated Pools. For example, PySpark development and debugging would be much easier if done from ADS.
July 21, 2022
Plays with Power BI nicely
- They unify many data sources easily
- There is some "code free" ETL work it enables
- There is some AI integration that works nice
- The cost structure is difficult to understand
- The job scheduling capabilities aren't easy to use
- The logging metrics aren't easy to see
March 17, 2022
Azure Synapse Does It All
- Data integration via poly base
- Data distribution
- Create table as select
- Resource allocation via user groups (for production ETL and report users)
- Integrating external 3rd party data sources is very easy in Snowflake and it’s missing in Azure Synapse
- Master data services and data quality services are missing in Azure Synapse. They are useful features present in on Orem Sql server
- Resource usage reports (top 10 expensive queries, most frequently run queries, etc) are a feature that can be added in Azure Synapse. It’s present in an on-prem SQL server. DMVs are there but viewing it visually as a report is more helpful.
- Create data pipelines to connect with multiple data workspace(s) and external data
- Ability to connect with Azure Data Lake (sequentially) for data warehousing
- Being able to manage connections and create integration runtimes (for onPrem data capture)
- Thus far haven't seen any complications and/or any missing features
November 30, 2021
Satisfied DBA/Data engineer
- The combination of SQL/unstructured data
- Keeping things "complicated, but simple"; [heterogeneous] data formats seen as just SQL tables to business experts used to use Power BI, Excel, and any other traditional SQL-oriented BI tools
- Integration options using "Synapse pipelines", the application of ADFs
- The greatly integrated solution of independent things (Spark MPP cluster, MPP SQL Servers, ADFs) - all sitting under one roof. Great job!
- Integration with super-fast, globally replicated data. I really appreciate the integration of NoSQL databases (namely Core API and Mongo API under Cosmos DB) with purely batch-processed BI data
- I have no idea right now. But... Synapse Analytics are typically seen as batch-processing of source data. What about tighter cooperation with streaming features like Event Hubs?
October 21, 2021
Azure Synapse Analytics - more powerful SQL for data warehousing
- fast query results
- integrated systems
- one application/area for all processes
- Delta Lake doesn't have full capabilities yet
- spark doesn't yet have delta live tables
- coding differences from Databricks' spark aren't well documented
August 25, 2021
Modern Database
- Easy to Manage data
- Blazing fast query processing
- Supports Modern fileformats
- Documentation and Usecases
- Pricing
- Admin capabilities
July 22, 2016
SQL Data Warehouse- everything you need to know
- It is very cost-effective
- Development time needed was much less in comparison to other systems
- Played very nicely with our ETL and OLAP reporting tools
- More features would be a plus
- I would like to see Microsoft offer some diagramming tools for data warehouse
- I believe processing time and speed could always be improved
July 15, 2016
Better than querying off your OLTP
- Quick to return data. Queries in a SQL data warehouse architecture tend to return data much more quickly than a OLTP setup. Especially with columnar indexes.
- Ability to manage extremely large SQL tables. Our databases contain billions of records. This would be unwieldy without a proper SQL datawarehouse
- Backup and replication. Because we're already using SQL, moving the data to a datawarehouse makes it easier to manage as our users are already familiar with SQL.
- It takes some time to setup a proper SQL Datawarehouse architecture. Without proper SSIS/automation scripts, this can be a very daunting task.
- It takes a lot of foresight when designing a Data Warehouse. If not properly designed, it can be very troublesome to use and/or modify later on.
- It takes a lot of effort to maintain. Businesses are continually changing. With that, a full time staff member or more will be required to maintain the SQL Data Warehouse.