Report:
The Forrester Wave™: Cloud Data Pipelines, Q4 2023
How does Forrester define the Cloud Data Pipelines market in 2023?
Organizations want simple, integrated, cost-effective, and highly automated solutions to support modern business insights. Cloud data pipelines (CDPs) help enterprises build analytics quickly, automate ingestion and data processing workflows, leverage new data sources, and support new business requirements. Enterprises need a data pipeline solution that delivers performance at scale, makes data engineers, data scientists, data analysts, and developers more productive, supports more complex use cases, and leverages new generative AI (genAI) capabilities to automate deployments.
Key Facts for The Forrester Wave™: Cloud Data Pipelines, Q4 2023 in 2023
- Publication Date: 27-Nov-2023
- Document ID: RES178461
- Summary: In our 26-criterion evaluation of cloud data pipeline providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps data management professionals select the right one for their needs.
- Authors: Noel Yuhanna, Aaron Katz, Caroline Provost, Jen Barton
How did the Cloud Data Pipelines market evolve in 2023?
- Organizations want simple, integrated, cost-effective, and highly automated solutions to support modern business insights
- Cloud data pipelines help enterprises build analytics quickly, automate ingestion and data processing workflows, leverage new data sources, and support new business requirements
- Enterprises need data pipeline solutions that deliver performance at scale and make data engineers, data scientists, data analysts, and developers more productive
- Cloud data pipeline vendors are offering advanced capabilities for roles across the enterprise to quickly develop, deploy, and manage data pipelines
- Key market demands include performance at the speed of business, multipersona support with personalized UI, and generative AI capabilities to automate deployments
- Solutions must support real-time analytics by streaming data quickly across on-premises, multiple clouds, and edge environments
- Vendors are responding with deep integration with serverless and Kubernetes, in-memory processing, and automated performance optimization
- The evaluation includes 15 providers assessed across current offering, strategy, and market presence
- Leaders include Confluent, Databricks, Informatica, Oracle, and Microsoft
What product features are required to be included in this year's evaluation?
- Enterprise data pipelining capabilities. The CDP has capabilities to ingest, process, transform, orchestrate, and deliver data to various endpoints. In addition, it has capabilities to support resilience and tools to manage, monitor, and troubleshoot data pipelines.
- Ability to develop and deploy in the public cloud. The vendors included in this evaluation provide CDP services or software in the public cloud for user organizations to implement and integrate with their data stack and applications.
- Support for a broad set of use cases. The CDP has customers using the solution in a scaled production environment for one or more of the following use cases: data integration, data engineering, data warehouse automation, and real-time analytics.
- Forrester mindshare. We only included vendors that have been mentioned through Forrester enterprise client interactions calls related to cloud data pipeline topics during the past 12 months.
What are the common features of top products in the Cloud Data Pipelines space?
No common features specified.
Scope Exclusions
- Vendors without enterprise data pipelining capabilities for ingesting, processing, transforming, orchestrating, and delivering data
- Solutions that cannot develop and deploy in public cloud environments
- Vendors without customers using the solution in scaled production environments
- Vendors not mentioned in Forrester enterprise client interactions related to cloud data pipeline topics in the past 12 months
- Solutions lacking capabilities to support resilience and tools to manage, monitor, and troubleshoot data pipelines
Inclusion Criteria
Vendors must, among other requirements:
- Enterprise data pipelining capabilities to ingest, process, transform, orchestrate, and deliver data to various endpoints
- Ability to develop and deploy in the public cloud
- Support for a broad set of use cases in scaled production environments
- Forrester mindshare through enterprise client interactions in the past 12 months
Offering Strengths — Relative Weighting
- Data connectivity and delivery — 20%
- Development — 15%
- Data processing — 20%
- Data management — 15%
- Data security and governance — 15%
- Deployment — 15%
Strategy Strength — Relative Weighting
- Vision — 30%
- Innovation — 25%
- Roadmap — 25%
- Partner ecosystem — 10%
- Adoption — 5%
- Pricing flexibility and transparency — 5%
FAQs
Q: What does this research cover?
A: This research covers a comprehensive 26-criterion evaluation of cloud data pipeline providers, examining their capabilities in data connectivity and delivery, development, data processing, data management, data security and governance, and deployment. The evaluation assesses vendor strategies including vision, innovation, roadmap, partner ecosystem, adoption, and pricing. It includes analysis of 15 significant vendors categorized as Leaders, Strong Performers, Contenders, and Challengers.
Q: Who should use this research?
A: This research should be used by data management professionals, data engineers, data scientists, data analysts, and IT decision-makers who are evaluating and selecting cloud data pipeline solutions for their organizations. It helps buyers understand how vendors compare across key capabilities, identify which providers best fit their specific needs (such as hybrid cloud deployment, high-performance requirements, lakehouse architecture, or multicloud environments), and make informed purchasing decisions based on current offerings, vendor strategies, and market positioning.
Q: What are the mandatory features of vendors included in this market?
A: Vendors must have enterprise data pipelining capabilities to ingest, process, transform, orchestrate, and deliver data to various endpoints, with capabilities to support resilience and tools to manage, monitor, and troubleshoot data pipelines. They must provide CDP services or software deployable in the public cloud for integration with data stacks and applications. Vendors must have customers using the solution in scaled production environments for use cases including data integration, data engineering, data warehouse automation, and real-time analytics. Additionally, vendors must have been mentioned in Forrester enterprise client interactions related to cloud data pipeline topics during the past 12 months.
Q: What are some reasons for not being included in this report?
A:
- Lack of enterprise data pipelining capabilities for ingestion, processing, transformation, orchestration, and delivery
- Inability to develop and deploy in public cloud environments
- No customers using the solution in scaled production environments for relevant use cases
- Not mentioned in Forrester enterprise client interactions related to cloud data pipeline topics in the past 12 months
- Missing capabilities to support resilience and tools to manage, monitor, and troubleshoot data pipelines
- Insufficient support for use cases such as data integration, data engineering, data warehouse automation, or real-time analytics
Q: What should buyers consider when evaluating products in this market?
A:
- Deliver performance at the speed of business with deep integration with serverless and Kubernetes, in-memory processing, built-in automated performance optimization, and ability to scale-up/scale-down system resources
- Offer support for multiple personas with personalized UI for technical and nontechnical users, including data engineers, data scientists, data analysts, developers, and business analysts
- Leverage generative AI to automate and accelerate development and deployment through integration with LLMs such as Dolly, Llama 2, OpenAI, and conversational interfaces
- Ensure vendor has production-ready generative AI capabilities they can demonstrate and a strong roadmap for genAI and LLM
- Evaluate support for real-time analytics use cases such as real-time customer 360, fraud detection, and IoT analytics
- Consider team collaboration features to accelerate use cases across different personas
- Assess vendor's ability to handle data whether on-premises, in multiple clouds, or at the edge
Q: How has the Cloud Data Pipelines market evolved in 2023?
A:
- Performance at scale for real-time analytics by streaming data quickly across on-premises, multiple clouds, and edge environments
- Support for multiple personas with personalized UI, enabling nontechnical users like business analysts and data analysts to build pipelines
- Leveraging generative AI to automate and accelerate development and deployment through natural language prompts and integration with LLMs
- Deep integration with serverless and Kubernetes architectures
- In-memory processing with built-in automated performance optimization and load balancing
- Team collaboration features to accelerate use cases across different roles
- Conversational interfaces to discover data and metadata and generate text-to-SQL
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Current Offering evaluates each vendor's position on the vertical axis and indicates the strength of its current offering through key capabilities including data connectivity and delivery, development, data processing, data management, data security and governance, and deployment. Strategy evaluates placement on the horizontal axis and indicates the strength of vendors' strategies through vision, innovation, roadmap, partner ecosystem, adoption, and pricing flexibility and transparency.
Reference
- Forrester, The Forrester Wave™: Cloud Data Pipelines, Q4 2023, 27-Nov-2023, ID RES178461
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