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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Grooper vs KNIME

Grooper vs KNIME

OverviewComparisonAlternatives

Overview

Grooper
Grooper
Stacks1
Followers2
Votes0
KNIME
KNIME
Stacks53
Followers46
Votes0

Grooper vs KNIME: What are the differences?

What is Grooper? 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.

What is KNIME? Create and productionize data science using one easy and intuitive environment. It is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept.

Grooper and KNIME belong to "Data Science Tools" category of the tech stack.

Some of the features offered by Grooper are:

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

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

  • Access, merge, and transform all of your data
  • Make sense of your data with the tools you choose
  • Support enterprise-wide data science practices

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Detailed Comparison

Grooper
Grooper
KNIME
KNIME

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.

It is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept.

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
Access, merge, and transform all of your data; Make sense of your data with the tools you choose; Support enterprise-wide data science practices; Leverage insights gained from your data
Statistics
Stacks
1
Stacks
53
Followers
2
Followers
46
Votes
0
Votes
0
Integrations
Alfresco
Alfresco
OneDrive
OneDrive
Microsoft SharePoint
Microsoft SharePoint
Python
Python
Apache Spark
Apache Spark
R Language
R Language
TensorFlow
TensorFlow
Apache Hive
Apache Hive
Apache Impala
Apache Impala
Keras
Keras
H2O
H2O

What are some alternatives to Grooper, KNIME?

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

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.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Apache Impala

Apache Impala

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

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