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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data As A Service
  5. Azure HDInsight vs Grooper

Azure HDInsight vs Grooper

OverviewComparisonAlternatives

Overview

Azure HDInsight
Azure HDInsight
Stacks29
Followers138
Votes0
Grooper
Grooper
Stacks1
Followers2
Votes0

Azure HDInsight vs Grooper: What are the differences?

Developers describe Azure HDInsight as "A cloud-based service from Microsoft for big data analytics". It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data. On the other hand, Grooper is detailed as "Innovate workflows by integrating difficult data". It empowers rapid innovation for organizations processing and integrating large quantities of difficult data. Created by a team of courageous developers frustrated by limitations in existing solutions, It is an intelligent document and digital data integration platform. It combines patented and sophisticated image processing, capture technology, machine learning, and natural language processing.

Azure HDInsight belongs to "Big Data as a Service" category of the tech stack, while Grooper can be primarily classified under "Data Science Tools".

Some of the features offered by Azure HDInsight are:

  • Fully managed
  • Full-spectrum
  • Open-source analytics service in the cloud for enterprises

On the other hand, Grooper provides the following key features:

  • Text and Document Classification
  • Hierarchical Data Modeling
  • Image Capture

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Detailed Comparison

Azure HDInsight
Azure HDInsight
Grooper
Grooper

It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data.

It empowers rapid innovation for organizations processing and integrating large quantities of difficult data. Created by a team of courageous developers frustrated by limitations in existing solutions, It is an intelligent document and digital data integration platform. It combines patented and sophisticated image processing, capture technology, machine learning, and natural language processing.

Fully managed; Full-spectrum; Open-source analytics service in the cloud for enterprises
Text and Document Classification; Hierarchical Data Modeling; Image Capture; Electronic Document Handling; Image Processing and Computer Vision; OCR; Data Extraction; Machine Learning; Natural Language Processing; Fuzzy Data Handling; Data Output; Document Rendering
Statistics
Stacks
29
Stacks
1
Followers
138
Followers
2
Votes
0
Votes
0
Integrations
IntelliJ IDEA
IntelliJ IDEA
Apache Spark
Apache Spark
Kafka
Kafka
Visual Studio Code
Visual Studio Code
Hadoop
Hadoop
Apache Storm
Apache Storm
HBase
HBase
Apache Hive
Apache Hive
Azure Data Factory
Azure Data Factory
Azure Active Directory
Azure Active Directory
Alfresco
Alfresco
OneDrive
OneDrive
Microsoft SharePoint
Microsoft SharePoint

What are some alternatives to Azure HDInsight, Grooper?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

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