Informatica is ranked as the no. 2 Events Stream Processing Platform provider in the latest Gartner “Market Share Analysis: Event Stream Processing Platforms, Worldwide, 2020 report.”  The report shows that Informatica has 5.6% of overall market share. In the total market size of the top 10 named vendors, Informatica has 12% of the market.
Informatica is on a mission to help customers simplify, drive greater productivity, and scale their data integration and data management capabilities. We continue to make great progress on our innovative Informatica Intelligent Data Management Cloud (IDMC) platform. Gartner and our customers are recognizing and valuing our investments in the data management space by ranking us as a leader in the event stream processing platform market.
Our leadership position reflects the value of Informatica’s AI-powered cloud-ready Data Engineering Streaming (DES) product and cloud-first, cloud-native Cloud Mass Ingestion (CMI) services. DES is a code-free or low-code stream processing solution that helps businesses implement real-time analytics use cases both on-premises and in hybrid multi-cloud environments. CMI is a code-free data ingestion solution that helps businesses continuously ingest and synchronize data from on-premises and cloud data sources, including databases, data lakes, files, and real-time event streams.
Strategic and Industry Use Cases for Data Streaming and Mass Ingestion
Informatica is seeing demand for streaming and mass ingestion across industries such as banking, retail, healthcare, manufacturing, insurance, and pharma. Organizations are leveraging Informatica’s Intelligent Data Management Cloud platform to solve strategic use cases such as:
- Data warehouse migration to the cloud
- Real-time offer management
- Real-time customer fraud analytics
- Predictive maintenance and smart factory
- Clinical research optimization
Informatica’s streaming and mass ingestion solutions are key elements of a sense, reason, and act reference architecture framework that enables customers to continuously ingest and process data from various streaming sources by leveraging open-source technologies like Apache Spark and Apache Kafka. Data Engineering Streaming provides out-of-the-box capabilities to parse, filter, enrich, aggregate, and cleanse streaming data while also helping to operationalize machine learning models on streaming data. With these capabilities, customers can also perform real-time analytics on change data capture (CDC) data to address their streaming analytics use cases.
8 Key Differentiators of Informatica’s Data Streaming and Mass Ingestion Solutions
Here are some of the key differentiating capabilities and features of Informatica’s streaming and mass ingestion solution:
- Built on open-source Spark streaming and supports other technologies like Apache Kafka, Azure Databricks, and Databricks Delta
- Unified design and monitoring experience to design and develop batch and streaming data pipelines
- Flexible, agnostic, and supports on-premises, hybrid, and multi-cloud deployments
- Improves developer productivity by enabling low-code, no-code streaming, and batch integration
- Out-of-the-box connectivity to various messaging sources like Kafka, JMS, Confluent, Azure EventHub, Amazon Kinesis, and Google Pub/Sub
- Real-time enrichment and model invocation withLookups, Windowing, Filter, Expression, Union, Router, Aggregate, Joiner, Sorter, Rank, Data Quality, Masking, Python, Java
- Governance for mission-critical streaming pipelines with end-to-end data lineage
- Wizard-based cloud-native mass ingestion from various sources like sensors, IoT edge devices, change data capture, clickstream, etc.
Graphic created by Informatica based on Gartner research.
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 Gartner, Market Share Analysis: Event Stream Processing Platforms, Worldwide, 2020, Fabrizio Biscotti, et al, 13 May 2020