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.
$4,700
per month 5000 Synapse Commit Units (SCUs)
IBM Informix
Score 9.9 out of 10
N/A
Informix is an embedded relational database offering from IBM.
It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.
IBM Informix creates an effective and secure channel for easy and quick data management and transfer across other major Cloud platforms and other data storage systems. The analytical ability is also the best and most effective visual functionalities and the encryption and the data archiving functionalities are great and easy on reporting.
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.
Excellent Data Warehouse performance from the basic engine. Outstanding Data Warehouse performance from the Informix Warehouse Accelerator module.
Best embedability among major RDBMS systems.
Scalable from the smallest Raspberry PI up to the largest monolithic systems and out to dozens of distributed nodes.
Hybrid data capabilities to merge relational data with time seriesv, geospacial data, JSON data and other non-traditional data types with performance comparable or better than systems dedicated to those data types.
With Azure, it's always the same issue, too many moving parts doing similar things with no specialisation. ADF, Fabric Data Factory and Synapse pipeline serve the same purpose. Same goes for Fabric Warehouse and Synapse SQL pools.
Could do better with serverless workloads considering the competition from databricks and its own fabric warehouse
Synapse pipelines is a replica of Azure Data Factory with no tight integration with Synapse and to a surprise, with missing features from ADF. Integration of warehouse can be improved with in environment ETl tools
It is very difficult to find a missing functionality in Informix, technically is great. I will again criticize the business side and how it has been managed over the past, I hope this could be improved with HCL's help. I know they are working hard, but we need to start letting the world know and revert their concept about its existence and that it is one of the best competitors within the data treatment, in the market. We need to start telling the world about success cases and stories showing this and backing up its strong technology.
The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.
Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.
In comparing Azure Synapse to the Google BigQuery - the biggest highlight that I'd like to bring forward is Azure Synapse SQL leverages a scale-out architecture in order to distribute computational processing of data across multiple nodes whereas Google BigQuery only takes into account computation and storage.
IBM Informix creates effective solutions for big data extraction and data transportation functionalities across the entire Cloud services and the Automation ability is the best. The security that IBM Informix provides for all our business data and other project information and contacts is effective and the reports are very clean and easy to understand.
Licensing fees is replaced with Azure subscription fee. No big saving there
More visibility into the Azure usage and cost
It can be used a hot storage and old data can be archived to data lake. Real time data integration is possible via external tables and Microsoft Power BI
Although I do not own nor have visibility on my company's figures:
Informix generates consistent savings on DBA staffing, no need for many DBAs as other DBMS require.
The replication architecture allowed consistent savings in the infrastructure as well as developments and maintenance, the job is already done, no need to develop complex and costly solutions, it's just a matter of configuring it.
The advantages of hybrid development (i.e mixing SQL and NoSQL in the same database) is not just a marketing hype: it allowed us to solve with a brilliant solution, in one afternoon of coding, a functional problem we have been having for more than 10 years!
The biggest drawback is that IBM pricing may be constraining, it has too important gaps between the mid range and highrange in terms of pricing
