Apache Spark for Azure HDInsight
This article provides an introduction to Spark in HDInsight and the different scenarios in which you can use Spark cluster in HDInsight.
Some of the top features or benefits of Apache Spark for Azure HDInsight are: Scalability, Integration with other Azure Services, Real-time Data Processing, Ease of Use, and Support for Multiple Languages. You can visit the info page to learn more.
Apache Spark for Azure HDInsight Alternatives & Competitors
The best Apache Spark for Azure HDInsight alternatives based on verified products, community votes, reviews and other factors.
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Open-Source Alternatives.
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Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.
Key Snowflake features:
Scalability Performance Ease of Use Data Sharing
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A fully managed data warehouse for large-scale data analytics.
Key Google BigQuery features:
Scalability Speed Integrations Automatic Optimization
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Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface.
Key Draxlr features:
Dashboards and Visualizations Slack Notifications Email notifications Query Builder
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Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Key Databricks features:
Unified Data Analytics Platform Scalability Collaborative Environment Performance Optimization
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Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Key Qubole features:
Scalability Multi-cloud Support Unified Interface Cost Management
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Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Key Amazon EMR features:
Scalability Cost-effectiveness Ease of Use Managed Service
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Azure HDInsight is a managed Apache Hadoop cloud service that lets you run Apache Spark, Apache Hive, Apache Kafka, Apache HBase, and more.
Key Azure HDInsight features:
Scalability Managed Service Cost-effectiveness Integration with Azure Ecosystem
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Snowplow is an enterprise-strength event analytics platform.
Key Snowplow features:
Data Ownership Flexibility Real-time Analytics Open Source
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Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Key Google Cloud Dataflow features:
Scalability Fully Managed Unified Programming Model Integration
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Apache Beam provides an advanced unified programming model to implement batch and streaming data processing jobs.
Key Apache Beam features:
Unified Model Portability Rich SDKs Windowing and Triggering
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The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...
Key HortonWorks Data Platform features:
Open Source Foundation Enterprise-Grade Security Scalability Comprehensive Ecosystem
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Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost.
Key Google Cloud Dataproc features:
Managed Service Integration with Google Cloud Scalability Cost Efficiency
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Azure Data Lake Storage Gen2 is highly scalable and secure storage for big data analytics. Maximize costs and efficiency through full integrations with other Azure products.
Key Azure Data Lake Store features:
Scalability Cost-effectiveness Integration with Azure Ecosystem Security Features
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Apache Storm is a free and open source distributed realtime computation system.
Key Apache Storm features:
Real-Time Processing Scalability Fault Tolerance Broad Language Support
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