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Azure Synapse Analytics VS IBM DataStage

Compare Azure Synapse Analytics VS IBM DataStage and see what are their differences

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Azure Synapse Analytics logo Azure Synapse Analytics

Get started with Azure SQL Data Warehouse for an enterprise-class SQL Server experience. Cloud data warehouses offer flexibility, scalability, and big data insights.

IBM DataStage logo IBM DataStage

Extract, transfer and load ETL data across multiple systems, with support forextended metadata management and big data enterprise connectivity.
  • Azure Synapse Analytics Landing page
    Landing page //
    2023-03-23
  • IBM DataStage Landing page
    Landing page //
    2023-07-15

Azure Synapse Analytics features and specs

  • Integration
    Azure Synapse Analytics integrates with other Azure services like Azure Data Lake Storage, Power BI, and Azure Machine Learning, enabling seamless data movement and business intelligence processes.
  • Scalability
    It allows on-demand scalability, both horizontally and vertically, providing the flexibility to handle workloads of any size efficiently.
  • Unified Experience
    Offers a unified interface for data ingestion, preparation, management, and serving, simplifying data operations and reducing the need for multiple tools.
  • Advanced Security
    Includes robust security features like encryption, network protection, and advanced threat protection to ensure data security and compliance.
  • Serverless and Dedicated Options
    Provides both serverless and dedicated resource models, allowing businesses to optimize their costs by selecting the appropriate compute resources for their needs.

Possible disadvantages of Azure Synapse Analytics

  • Complexity
    The comprehensive range of features and tools can lead to a steep learning curve and complexity in setup and management for new users.
  • Cost Management
    Although flexibility is offered, managing and predicting costs can be challenging, especially in serverless scenarios where usage might fluctuate.
  • Resource Limitations
    Despite its scalability, there might be certain limitations in terms of data size or query complexity compared to some on-premises solutions.
  • Dependency on Internet Connectivity
    As a cloud-based solution, it requires stable and reliable internet connectivity, which may not be available in all regions or circumstances.
  • Integration Learning Curve
    While integration is a strength, mastering the integration with various Azure services and third-party tools can require substantial time and effort.

IBM DataStage features and specs

  • Scalability
    IBM DataStage provides robust scalability, allowing organizations to process and transform large volumes of data efficiently. This makes it suitable for enterprises with extensive data integration needs.
  • Integration Capabilities
    DataStage offers comprehensive integration capabilities with a wide range of data sources and targets, including cloud-based and on-premises systems, facilitating seamless data movement and transformation.
  • High Performance
    The platform is optimized for high performance, supporting parallel processing and workload management, which helps in processing large datasets quickly and effectively.
  • User-Friendly Interface
    IBM DataStage provides an intuitive graphical interface that simplifies the design and management of data integration tasks, making it accessible to both technical and non-technical users.
  • Comprehensive Metadata Management
    It offers robust metadata management features, helping users maintain, analyze, and govern their data assets effectively, which enhances data quality and compliance.

Possible disadvantages of IBM DataStage

  • High Cost
    The licensing and operational costs of IBM DataStage can be relatively high, making it a less viable option for smaller businesses or organizations with budget constraints.
  • Complex Setup
    Setting up DataStage can be complex and time-consuming, requiring significant technical expertise, which might be challenging for organizations without skilled IT staff.
  • Steep Learning Curve
    Despite its user-friendly interface, mastering the full capabilities of DataStage can take time, and users may need extensive training to utilize all features effectively.
  • Resource Intensive
    The platform can be resource-intensive, demanding considerable hardware and system resources to perform optimally, which might not be feasible for all organizations.
  • Dependency on IBM Ecosystem
    Organizations heavily investing in IBM DataStage might find themselves increasingly reliant on IBM's ecosystem, which could limit flexibility in choosing other solutions without significant migration efforts.

Azure Synapse Analytics videos

+ Add

Azure Synapse Analytics - Next-gen Azure SQL Data Warehouse

More videos:

  • Review - Is Azure SQL Data Warehouse the Right SQL Platform for You?

IBM DataStage videos

+ Add

IBM InfoSphere DataStage Skill Builder Part 1: How to build and run a DataStage parallel job

Category Popularity

0-100% (relative to Azure Synapse Analytics and IBM DataStage)

Azure Synapse Analytics

IBM DataStage

Office & Productivity
100 100%
Office & Productivity
0% 0
Data Integration
0 0%
Data Integration
100% 100
Development
72 72%
Development
28% 28
ETL
0 0%
ETL
100% 100

User comments

Share your experience with using Azure Synapse Analytics and IBM DataStage. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Azure Synapse Analytics and IBM DataStage

Azure Synapse Analytics Reviews

Data Warehouse Tools
Azure Synapse Analytics (formerly Azure Data Warehouse) is a cloud-native data warehouse integrated with other Azure services. It unifies data warehousing and big data analytics for comprehensive insights, offering visually interactive tools for user-friendly data exploration.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
Azure Synapse analytics is scalable for large data tables based on its distributed computing. It relies on the MPP (mentioned in the beginning, revisit if you did not grasp it) to quickly run high volumes of complex queries across multiple nodes. With Synapse, there’s an extra emphasis on security and privacy.
Source: geekflare.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
Azure SQL Data Warehouse, now subsumed by Azure Synapse Analytics, brings together the worlds of big data analytics and enterprise data warehousing. Over the years, Azure has made a name for enabling the seamless transfer of data between on-premise and cloud ecosystems.
Source: blog.panoply.io

IBM DataStage Reviews

Best ETL Tools: A Curated List
IBM InfoSphere DataStage is an enterprise-level ETL tool that is part of the IBM InfoSphere suite. It is engineered for high-performance data integration and can manage large data volumes across diverse platforms. With its parallel processing architecture and comprehensive set of features, DataStage is ideal for organizations with complex data environments and stringent data...
Source: estuary.dev
10 Best ETL Tools (October 2023)
IBM DataStage is an excellent data integration tool that is focused on a client-server design. It extracts, transforms, and loads data from a source to a target. These sources can include files, archives, business apps, and more.
Source: www.unite.ai
A List of The 16 Best ETL Tools And Why To Choose Them
Infosphere Datastage is an ETL tool offered by IBM as part of its Infosphere Information Server ecosystem. With its graphical framework, users can design data pipelines that extract data from multiple sources, perform complex transformations, and deliver the data to target applications.
Source: www.datacamp.com
Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
DataStage is an IBM proprietary tool that extracts, transforms, and loads data from a source to the destination storage. It is suitable for on-premises deployment and use in hybrid or multi-cloud environments. Data sources that DataStage is compatible with include sequential files, indexed files, relational databases, external data sources, archives, enterprise applications,...
Source: visual-flow.com

Social recommendations and mentions

Based on our record, Azure Synapse Analytics seems to be more popular. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Azure Synapse Analytics mentions (4)

  • DbVisualizer 24.2: A Complete Review
    Azure Synapse Analytics: DbVisualizer now has extended support for dedicated and serverless SQL pools in Azure Synapse Analytics. That includes support for database-scoped credentials, external file formats and data sources, and external tables. For more information, see the Azure Synapse Dedicated and Azure Synapse Serverless pages on the official site. - Source: dev.to / 9 months ago
  • Deploying a Data Warehouse with Pulumi and Amazon Redshift
    A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of... - Source: dev.to / over 2 years ago
  • [WSJ] Facebook Parent Meta Expected to Post Slowest Revenue Growth Since IPO
    You don't run into these kinds of problems with other tools, like the ones I mentioned. I've never tried the Azure ones, but my gut says they may have some scaling issues (synapse analytics looks promising but I have no experience with it). Source: about 3 years ago
  • The Difference Between Data Warehouses, Data Lakes, and Data Lakehouses.
    Popular managed cloud data warehouse solutions include Azure Synapse Analytics, Azure SQL Database, and Amazon Redshift. - Source: dev.to / about 3 years ago

IBM DataStage mentions (0)

We have not tracked any mentions of IBM DataStage yet. Tracking of IBM DataStage recommendations started around Mar 2021.

What are some alternatives?

When comparing Azure Synapse Analytics and IBM DataStage, you can also consider the following products

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.

Azure Data Factory - Learn more about Azure Data Factory, the easiest cloud-based hybrid data integration solution at an enterprise scale. Build data factories without the need to code.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Striim - Striim provides an end-to-end, real-time data integration and streaming analytics platform.

Databricks Unified Analytics Platform - One platform for accelerating data-driven innovation across data engineering, data science & business analytics

HVR - Your data. Where you need it. HVR is the leading independent real-time data replication solution that offers efficient data integration for cloud and more.

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