Cloudera CDH vs IBM InfoSphere BigInsights

Struggling to choose between Cloudera CDH and IBM InfoSphere BigInsights? Both products offer unique advantages, making it a tough decision.

Cloudera CDH is a Ai Tools & Services solution with tags like hadoop, hdfs, yarn, spark, hive, hbase, impala, kudu.

It boasts features such as HDFS - Distributed and scalable file system, YARN - Cluster resource management, MapReduce - Distributed data processing, Hive - SQL interface for querying data, HBase - Distributed column-oriented database, Impala - Massively parallel SQL query engine, Spark - In-memory cluster computing framework, Kudu - Fast analytics on fast data, Cloudera Manager - Centralized management and monitoring and pros including Open source and free to use, Includes many popular Hadoop ecosystem projects, Centralized management and monitoring, Pre-configured and tested combinations of components, Active development and support from Cloudera.

On the other hand, IBM InfoSphere BigInsights is a Ai Tools & Services product tagged with hadoop, big-data, analytics, unstructured-data.

Its standout features include Distributed processing of large data sets across clusters using Hadoop MapReduce, Supports variety of data sources like HDFS, HBase, Hive, text files, Web console for managing Hadoop clusters and jobs, Text analytics and natural language processing tools, Connectors for integrating with SQL and NoSQL databases, Enterprise security features like Kerberos authentication, Analytics tools like BigSheets and Big SQL, and it shines with pros like Scalable and flexible for analyzing large volumes of data, Supports real-time analysis with HBase integration, Simplified Hadoop management through web UI, Advanced analytics capabilities beyond just MapReduce, Integrates with existing data sources and BI tools, Mature enterprise software backed by IBM support.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Cloudera CDH

Cloudera CDH

Cloudera CDH (Cloudera Distribution Including Apache Hadoop) is an open source data platform that combines Hadoop ecosystem components like HDFS, YARN, Spark, Hive, HBase, Impala, Kudu, and more into a single managed platform.

Categories:
hadoop hdfs yarn spark hive hbase impala kudu

Cloudera CDH Features

  1. HDFS - Distributed and scalable file system
  2. YARN - Cluster resource management
  3. MapReduce - Distributed data processing
  4. Hive - SQL interface for querying data
  5. HBase - Distributed column-oriented database
  6. Impala - Massively parallel SQL query engine
  7. Spark - In-memory cluster computing framework
  8. Kudu - Fast analytics on fast data
  9. Cloudera Manager - Centralized management and monitoring

Pricing

  • Open Source
  • Subscription-Based (Cloudera Enterprise)

Pros

Open source and free to use

Includes many popular Hadoop ecosystem projects

Centralized management and monitoring

Pre-configured and tested combinations of components

Active development and support from Cloudera

Cons

Can be complex to configure and manage

Requires dedicated hardware/cluster

Steep learning curve for Hadoop and related technologies

Not as flexible as rolling your own Hadoop distribution


IBM InfoSphere BigInsights

IBM InfoSphere BigInsights

IBM InfoSphere BigInsights is a Hadoop-based software platform for analyzing large volumes of structured and unstructured data. It facilitates managing and analyzing Big Data.

Categories:
hadoop big-data analytics unstructured-data

IBM InfoSphere BigInsights Features

  1. Distributed processing of large data sets across clusters using Hadoop MapReduce
  2. Supports variety of data sources like HDFS, HBase, Hive, text files
  3. Web console for managing Hadoop clusters and jobs
  4. Text analytics and natural language processing tools
  5. Connectors for integrating with SQL and NoSQL databases
  6. Enterprise security features like Kerberos authentication
  7. Analytics tools like BigSheets and Big SQL

Pricing

  • Subscription-Based
  • Pay-As-You-Go

Pros

Scalable and flexible for analyzing large volumes of data

Supports real-time analysis with HBase integration

Simplified Hadoop management through web UI

Advanced analytics capabilities beyond just MapReduce

Integrates with existing data sources and BI tools

Mature enterprise software backed by IBM support

Cons

Can be complex to configure and manage

Requires expertise in MapReduce and Hadoop

Not fully open source unlike Hadoop

Can be expensive compared to open source Big Data platforms

Steep learning curve for developers new to Hadoop