IBM Analytics Engine
Analytics Engine is a combined Apache Spark and Apache Hadoop service for creating analytics applications.
Some of the top features or benefits of IBM Analytics Engine are: Scalability, Integration with IBM Cloud, Support for Multiple Analytics Engines, Automated Management, and Cost Efficiency. You can visit the info page to learn more.
IBM Analytics Engine Alternatives & Competitors
The best IBM Analytics Engine alternatives based on verified products, community votes, reviews and other factors.
Filter:
12
Open-Source Alternatives.
Latest update:
-
A fully managed data warehouse for large-scale data analytics.
Key Google BigQuery features:
Scalability Speed Integrations Automatic Optimization
-
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
-
Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI.
Key Grapple features:
Automatic Data Refresh Universal Data Library Natural Language Map Data
-
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
-
Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โWhat is Apache Spark?
Key Databricks features:
Unified Data Analytics Platform Scalability Collaborative Environment Performance Optimization
-
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
-
Snowplow is an enterprise-strength event analytics platform.
Key Snowplow features:
Data Ownership Flexibility Real-time Analytics Open Source
-
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
-
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
-
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
-
Apache Beam provides an advanced unified programming modelย to implement batch and streaming data processing jobs.
Key Apache Beam features:
Unified Model Portability Rich SDKs Windowing and Triggering
-
This article provides an introduction to Spark in HDInsight and the different scenarios in which you can use Spark cluster in HDInsight.
Key Apache Spark for Azure HDInsight features:
Scalability Integration with other Azure Services Real-time Data Processing Ease of Use
-
Azure HDInsight is an Apache Hadoop distribution powered by the cloud.
Key Microsoft Azure HDInsight features:
Scalability Integration Open Source Ecosystem Managed Service
-
SQream empowers organizations to analyze the full scope of their Massive Data, from terabytes to petabytes, to achieve critical insights which were previously unattainable.
IBM Analytics Engine discussion
