Synapse Analytics vs SQL Server 2019 Big Data Cluster

Question

Could someone explain the difference between SQL Server 2019 BDC vs Azure Synapse Analytics other than OLAP & OLTP differences? Why would one use Analytics over SQL Server 2019 BDC?

Answer 1

I believe the user user3129206 is asking SQL Server 2019 BDC vs Azure Synapse Analytics not SQL Server vs Azure Synapse Analytics so the first answer is relevant.

The only thing I'd argue is that the BDC is also an MPP like Synapse because of Pods in Kubernetes if implemented right, with many servers + HDS.

I plan to test BDC on-premises and see how demanding the install and maintenance are. The neat thing about the BDC seems to be easy, partially or fully, to port it from on-premises to Azure or any cloud.

It seems that BDC is both OLTP and OLAP, trying to provide the best of both worlds.

As I am on the same comparison quest, I'll try to get back and share what I learn.

Answer 2

Azure Synapse Analytics is a Cloud based DWH with DataLake, ADF & PowerBI designers tightly integrated. it is a PaaS offering and it is not available on-prem. The DWH engine is MPP with limited polybase support (DataLake).

it also allows ypu to provision Apache Spark if needed.

SQLServer 2019 Big Data Cluster is a IaaS platform based on Kubernetes. it can be implemented on-prem on VMs or on OpenShift or on AKS Any cloud for that matter).

Its Data Virtualization support is very good with support for ODBC data sources and a Data Pool to support Data Virtualization- Implemented via Polybase.

Apache Spark makes up the Big Data compute.

Though it is not a MPP like Synapse, because of Pods in Kubernetes, multiple pods can be created on the fly through scalability features such as VMSS ... etc.

If you want Analytical capability on-prem you will use SQLServer 2019 BDC but if you want a Cloud based DWH with analytical capability features you will use Synapse

Answer 3

explain the difference between SQL Server 2019 BDC vs Azure Synapse Analytics

Server is OLTP and Synapse is OLAP. :D

other than OLAP & OLTP differences? Why would one use Analytics over SQL Server 2019 BDC?

Purely from a terminology point of view their product management have no clue what they are doing.

• "SQL Server" is a DYI/on-prem/managed-by-you DB.
• Fully Azure managed SaaS version of SQL Server is known as Azure SQL Database.
• They also have "Azure SQL Managed Instance", and "SQL Server on Azure VM".
• Azure Synapse is renamed Dedicated SQL-Pools.
• Azure Synapse On-demand is renamed to Serverless SQL-Pools.
• Azure Synapse Analytics = Dedicated + Serverless + bunch of ML services.

I'm going to answer assuming your question is:

Why would one use "Azure Synapse Dedicated or Serverless" over SQL Server?

• SQL Server is on prem DIY, other is SaaS, fully managed by Azure. With this comes all the pros/cons of SaaS like No CAPEX, no management, elastic, very large scale, ...
• Synapse' USP is it's MPP, which SQL Server does not have. Though I see things like Polybase and EXTERNAL TABLES being supported by SQL Server.
• Due to MPP architecture, Synapse's transactional performance is worst by far (that I've seen). E.g. Executing INSERT INTO xxx VALUES(...) to add one row via JDBC would take about 1-2 seconds as against 10-12 seconds for importing CSV files with 10s of thousands of rows using COPY command. And INSERT INTO does not scale with JDBC batching. It'll take 100 seconds to insert 100 rows in one batch.

It is not your fault that you are confused. IMO Azure Product Management for Databases (SQL Server, DW, ADP, Synapse, Analytics and the 10 other flavors of all these) have no clue what they want to offer 2 years from today. Every product boasts of Big Data, Massive this and that, ML and Analytics, Elastic this and that. Go figure.

PS: Check out Snowflake if you haven't.

I'm not affiliated with Microsoft or Snowflake.