[ Cloudera Reviews ](https://www.g2.com/products/cloudera/reviews) [ Cloudera Reviews ](https://www.g2.com/products/cloudera/reviews) # Cloudera Features ##### ## Reports (5) Reports Interface Reports interface for standard and self-service reports is intuitive and easy to use. Steps to Answer Requires a minimal number of steps/clicks to answer business question. Graphs and Charts Offers a variety of attractive graph and chart formats. Score Cards Score cards visually track KPI's. Dashboards Provides business users an interface to easily design, refine and collaborate on their dashboards Show More ##### ## Self Service (6) Calculated Fields Using formulas based on existing data elements, users can create and calculate new field values. Data Column Filtering Business users have the ability to filter data in a report based on predefined or automodeled parameters. Data Discovery Users can drill down and explore data to discover new insights. Search Ability to search global data set to find and discover data. Collaboration / Workflow Ability for users to share data and reports they have built within the BI tool and outside the tool through other collaboration platforms. Automodeling Tool automatically suggests data types, schemas and hierarchies. Show More ##### ## Advanced Analytics (3) Predictive Analytics Analyze current and historical trends to make predictions about future events. Data Visualization Communicate complex information clearly and effectively through advanced graphical techniques. Big Data Services Ability to handle large, complex, and/or siloed data sets. Show More ##### ## Building Reports (4) Data Transformation Converts data formats of source data into the format required for the reporting system without mistakes. Data Modeling Ability to (re)structure data in a manner that allows extracting insights fast and accurate. WYSIWYG Report Design Provides business users an interface to easily design and refine their dashboards and reports. (What You See Is What You Get) Integration APIs Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc with other software applications. Show More ##### ## Database Features (7) Storage Availability Stability Scalability Security Data Manipulation Query Language Show More ##### ## Model Development (5) Language Support Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript Drag and Drop Offers the ability for developers to drag and drop pieces of code or algorithms when building models Pre-Built Algorithms Provides users with pre-built algorithms for simpler model development Model Training Supplies large data sets for training individual models Feature Engineering Transforms raw data into features that better represent the underlying problem to the predictive models Show More ##### ## Machine/Deep Learning Services (6) Computer Vision Offers image recognition services Natural Language Processing Offers natural language processing services Natural Language Generation Offers natural language generation services Artificial Neural Networks Offers artificial neural networks for users Natural Language Understanding Offers natural language understanding services Deep Learning Provides deep learning capabilities Show More ##### ## Deployment (15) Managed Service Manages the intelligent application for the user, reducing the need of infrastructure Application Allows users to insert machine learning into operating applications Scalability Provides easily scaled machine learning applications and infrastructure Language Flexibility Allows users to input models built in a variety of languages. Framework Flexibility Allows users to choose the framework or workbench of their preference. Versioning Records versioning as models are iterated upon. Ease of Deployment Provides a way to quickly and efficiently deploy machine learning models. Scalability Offers a way to scale the use of machine learning models across an enterprise. On-Premise Provides On-Premise deployment options. Cloud Provides Cloud deployment options (private or public cloud, hybrid cloud). Language Flexibility Allows users to input models built in a variety of languages. Framework Flexibility Allows users to choose the framework or workbench of their preference. Versioning Records versioning as models are iterated upon. Ease of Deployment Provides a way to quickly and efficiently deploy machine learning models. Scalability Offers a way to scale the use of machine learning models across an enterprise. Show More ##### ## Database (3) Real-Time Data Collection Collects, stores, and organizes massive, unstructured data in real time Data Distribution Facilitates the disseminating of collected big data throughout parallel computing clusters Data Lake Creates a repository to collect and store raw data from sensors, devices, machines, files, etc. Show More ##### ## Integrations (2) Hadoop Integration Aligns processing and distribution workflows on top of Apache Hadoop Spark Integration Aligns processing and distribution workflows on top of Apache Hadoop Show More ##### ## Platform (3) Machine Scaling Facilitates solution to run on and scale to a large number of machines and systems Data Preparation Curates collected data for big data analytics solutions to analyze, manipulate, and model Spark Integration Aligns processing and distribution workflows on top of Apache Hadoop Show More ##### ## Processing (2) Cloud Processing Moves big data collection and processing to the cloud Workload Processing Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems Show More ##### ## Data Transformation (2) Real-Time Analytics Facilitates analysis of high-volume, real-time data. Data Querying Allows user to query data through query languages like SQL. Show More ##### ## Connectivity (4) Hadoop Integration Aligns processing and distribution workflows on top of Apache Hadoop Spark Integration Aligns processing and distribution workflows on top of Apache Spark Multi-Source Analysis Integrates data from multiple external databases. Data Lake Facilitates the dissemination of collected big data throughout parallel computing clusters. Show More ##### ## Operations (7) Data Visualization Processes data and represents interpretations in a variety of graphic formats. Data Workflow Strings together specific functions and datasets to automate analytics iterations. Governed Discovery Isolates certain datasets and facilitates management of data access. Notebooks Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations Metrics Control model usage and performance in production Infrastructure management Deploy mission-critical ML applications where and when you need them Collaboration Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Show More ##### ## Data Governance (3) User Access Management Allows administrators to assign role-based user access for specific data sets Dynamic Data Masking Hides and masks sensitive data automatically based on user permissions Data Lineage Provides historical insights into original data sources and transformations made to data sets Show More ##### ## Data Preparation (6) Search Offers simple search capabilities to discover specific data sets Data Quality and Cleansing Allows users and administrators to easily clean data to maintain quality and integrity Data Transformation Converts data formats of source data into the format required for the reporting system without mistakes Data Modeling Tools to (re)structure data in a manner that allows extracting insights quickly and accurately Connectors Ability to connect the analytics platform with a wide range of connector options for common data sources, including popular enterprise applications. Data Governance Connects to enterprise data governance software, or provides integrated data governance features to avoid misuse of data Show More ##### ## Collaboration (4) Commenting Allows users to comment on data sets to help future users better interact and interpret the data Profiling and Classification Permits profiling of data sets for increased organization, both by users and machine learning Business and Data Glossary Creates a business glossary for faster understanding by the average business user Metadata Management Indexes metadata descriptions for easier searching and enhanced insights Show More ##### ## Artificial Intelligence (3) Machine Learning Recommendations Automates recommendations for users based on machine learning functionality Natural Language Query Offers natural language querying functionality for non-technical users Automatic Data Cleansing Cleans data to improve quality via automation Show More ##### ## Administration (4) Data Modelling Tools to (re)structure data in a manner that allows extracting insights quickly and accurately Recommendations Analyzes data to find and recommend the highest value customer segmentations. Workflow Management Tools to create and adjust workflows to ensure consistency. Dashboards and Visualizations Presents information and analytics in a digestible, intuitive, and visually appealing way. Show More ##### ## Compliance (4) Sensitive Data Compliance Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards. Training and Guidelines Provides guidelines or training related to sensitive data compliance requirements, Policy Enforcement Allows administrators to set policies for security and data governance Compliance Monitoring Monitors data quality and send alerts based on violations or misuse Show More ##### ## Data Quality (3) Data Preparation Curates collected data for big data analytics solutions to analyze, manipulate, and model Data Distribution Facilitates the disseminating of collected big data throughout parallel computing clusters Data Unification Compile data from across all systems so that users can view relevant information easily. Show More ##### ## Management (19) Reporting View ETL process data via reports and visualizations like charts and graphs. Auditing Record ETL historical data for auditing and potential data correction needs. Cataloging Records and organizes all machine learning models that have been deployed across the business. Monitoring Tracks the performance and accuracy of machine learning models. Governing Provisions users based on authorization to both deploy and iterate upon machine learning models. Model Registry Allows users to manage model artifacts and tracks which models are deployed in production. Data dictionary Stores the database metadata, that is the definitions of data elements, types, relationships etc. Data Replication Creates a copy of the database to maintain consistency and integrity. Query Language Allows users to create, update and retrieve data in a database. Data Modeling Defines the logical design of the data before building the schemas. Performance Analysis Monitors and analyzes critical database attributes like query performance, user sessions, dead lock detail, system errors etc and visualize them on a custom dashboard. Business Glossary Lets users build a glossary of business terms, vocabulary and definitions across multiple tools. Data Discovery Provides a built-in integrated data catalog that allows users to easily locate data across multiple sources. Data Profililng Monitors and cleanses data with the help of business rules and analytical algorithms. Reporting and Visualization Visualize data flows and lineage that demonstrates compliance with reports and dashboards through a single console. Data Lineage Provides an automated data lineage functionality which provides visibility over the entire data movement journey from data origination to destination. Cataloging Records and organizes all machine learning models that have been deployed across the business. Monitoring Tracks the performance and accuracy of machine learning models. Governing Provisions users based on authorization to both deploy and iterate upon machine learning models. Show More ##### ## Functionality (5) Extraction Extract data from the designated source(s) like relational databases, JSON files, and XML files. Transformation Cleanse and re-format extracted data to the needed target format. Loading Load reformatted data into target database, data warehouse, or other storage location. Automation Arrange ETL processes to occur automatically on needed time schedule (e.g., daily, weekly, monthly). Scalability Capable of scaling processing power up or down based on ETL volume. Show More ##### ## System (1) Data Ingestion & Wrangling Gives user ability to import a variety of data sources for immediate use Show More ##### ## Data Modeling and Blending (3) Data Querying Using formulas based on existing data elements, users can create and calculate new field values Data Filtering Business users have the ability to filter data in a report based on predefined or automodeled parameters. Data Blending Allows the user to combine data from multiple sources into a functioning dataset. Show More ##### ## Data Management (16) Data Integration Consolidate data from various disparate sources in a single unified view Data Discovery Understand the state of data, applications, systems and services Multi - Platform Manage data across environments (on-premises cloud, hybrid, and multi-cloud) Metadata Provides metadata management and lineage capabilities Data Integration Consolidates, Cleanses and Normalizes data from multiple disparate sources. Data Compression Helps save storage capacity and improves query performance. Data Quality Eliminates data inconsistency and duplications ensuring data integrity. Built-In Data Analytics SQL based analytics functions like Time series, pattern matching, geospatial analytics etc. In-Database Machine Learning Provides built in capabilities like machine learning algorithms, data preparation functions, model evaluation and management etc. Data Lake Analytics Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS Data Model Stores data as key-value pairs where key is a unique identifier. Data Types Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc. Data Integration Integrates data and data-related technologies into a single environment. Metadata Provides metadata management capabilities. Self-service Empowers the user via a self-service capability to manage data workflows. Automated workflows Completely automates end-to-end data workflows across the data integration lifecycle. Show More ##### ## Analytics (3) Data Analytics Supports advanced analytics solutions for better business decision making Analytics capabilities Provides a high performance, flexibile analytics platform to support data management and embrace data driven decision making. Dasboard visualizations Collect and displays metrics across the data integration via a dashboard. Show More ##### ## Security (17) Compliance Rules and regulations inherited from source systems or defined to secure sensitive data Governance Grant or restrict data access and control Data Protection Built - In Backup and Disaster Recovery Data Encryption Encrypts and transforms data at the database from a readable state into a ciphertext of unreadable characters. User Access Control Allows restricted user acess to modify depending on the access level. Database Locking Prevents other users and applications from accessing data while it is being updated to avoid data loss or update. Access Control Allows permissions to be granted or revoked in the database, schema or table levels. Encryption Built-in native encryption with enterprise key management. Authentication Provides multi-factor authentication with certificates. Role-Based Authorization Provides predefined system roles, privileges, and user-defined roles to users. Authentication Allows integration with external security mechanisms like Kerberos, LDAP authentication etc. Encryption Provides encryption capability for all the data at rest using encryption keys. Data Governance Policies, procedures and standards to manage and access data. Data Security Restricts data access at a cell level, mask or hide parts of cells, and encrypt data at rest and in motion Access Control Authenticates and authorizes individuals to access the data they are allowed to see and use. Roles Management Helps identify and manage the roles of owners and stewards of data. Compliance Management Helps adhere to data privacy regulations and norms. Show More ##### ## Integration (3) AI/ ML Integration Integrates with data science workflows, Machine Learning and artificial intelligence (AI) capabilities. BI Tool Integration Integrates with BI Tools to transform data into Actionable Insights. Data lake Integration Provides speed in data processing and capturing unstructured, semi-structured and streaming data. Show More ##### ## Performance (6) Scalability Manages huge volumes of data, upscale or downscale as per demand. Disaster Recovery Provides data recovery functionality to protect and restore data in a database. Data Concurrency Allows multi-version concurrency control. Workload Management Handles workloads, from single machines to data warehouses or web services with many concurrent users. Advanced Indexing Allows users to quickly retrieve data through various types of indexing like B-tree, hash table etc. Query Optimizer Helps interpret SQL queries and determine the fastest method of execution. Show More ##### ## Maintenance (3) Data Migration Allows data movement from one database to another. Backup and Recovery Provides data backup and recovery functionality to protect and restore a database. Multi-User Environment Allows users to access and work on data concurrently, supporting several views of the data. Show More ##### ## Support (4) Text Search Provides support for international character sets and full text search. Data Types Supports multiple data types like primitive, structured, document etc. Languages Supports multiple procedural programming languages like PL/PGSQL, Perl, Python etc. Operating Systems Available on multiple operating systems like Linux, Windows, MacOS etc. Show More ##### ## Management (4) Data Schema Data is organized as a set of tables with columns and rows like a table structure. Query Language Allows users to create, update and retrieve data in a database. ACID - Complaint Adheres to ACID (atomicity, consistency, isolation, durability), a set of database transaction properties. Data Replication Provides log-based or/and trigger-based replication. Show More ##### ## Availability (3) Auto Sharding Implements auto horizontal data partitioning that allows storing data on more than one node to scale out. Auto Recovery Restores a database to a correct (consistent) state in the event of a failure. Data Replication Copy data across multiple servers through master-slave, peer-to-peer replication architecture etc. Show More ##### ## Support (2) Multi-Model Provides support to handle structured, semi-structured, and unstructured data with equal effect. Operating Systems Available on multiple operating systems like Linux, Windows, MacOS etc. Show More ##### ## Maintainence (2) Data Quality Management Defines, validates, and monitors business rules to safeguard master data readiness. Policy Management Allows users to create and review data policies to make them consistent across the organization. Show More ##### ## Monitoring and Management (2) Data Observability Involved solely in monitoring data pipelines, sending alerts and troubleshooting data. Testing capabilities Deploys testing capabilities such as report testing, big data testing, cloud data migration testing, ETL and data warehouse testing. Show More ##### ## Cloud Deployment (2) Hybrid cloud support Supports analytical platforms and data pipelines across complex hybrid environments. Cloud migration capabilities Supports migration of component or pipeline to different cloud environments. Show More ##### ## Data management (5) Metadata Management Indexes metadata descriptions for enhanced insights. Automation Features Ensures automation of metadata across the organization. Dynamically improves data management processes. Collaboration Embedded collaboration using APIs and in-app integrations. Data Lineage Provides insights into original data sources and transformations made to data sets from source to consumption of data. Data Discovery Provides an interface to collect and evaluate data to identfy patterns and outliers. Show More ##### ## Reporting (3) Intelligent Insights Constantly processes metadata to provide intelligent insights. Actionable Insights Provides actionable insights, and generates notifications and alerts to help teams make informed decisions. Dashboards Supports 360 degree data visibility via a single dashboard. Show More ##### ## Generative AI (19) AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text-to-Image Provides the ability to generate images from a text prompt. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. AI Text Generation Allows users to generate text based on a text prompt. AI Text Summarization Condenses long documents or text into a brief summary. Show More ##### ## Agentic AI - Machine Learning Data Catalog (5) Autonomous Task Execution Capability to perform complex tasks without constant human input Multi-step Planning Ability to break down and plan multi-step processes Cross-system Integration Works across multiple software systems or databases Adaptive Learning Improves performance based on feedback and experience Decision Making Makes informed choices based on available data and objectives Show More ##### ## Agentic AI - Data Governance (6) Autonomous Task Execution Capability to perform complex tasks without constant human input Multi-step Planning Ability to break down and plan multi-step processes Cross-system Integration Works across multiple software systems or databases Adaptive Learning Improves performance based on feedback and experience Natural Language Interaction Engages in human-like conversation for task delegation Decision Making Makes informed choices based on available data and objectives Show More ##### ## Agentic AI - Data Fabric (5) Autonomous Task Execution Capability to perform complex tasks without constant human input Multi-step Planning Ability to break down and plan multi-step processes Cross-system Integration Works across multiple software systems or databases Adaptive Learning Improves performance based on feedback and experience Decision Making Makes informed choices based on available data and objectives Show More ##### ## Agentic AI - DataOps Platforms (5) Autonomous Task Execution Capability to perform complex tasks without constant human input Multi-step Planning Ability to break down and plan multi-step processes Cross-system Integration Works across multiple software systems or databases Adaptive Learning Improves performance based on feedback and experience Decision Making Makes informed choices based on available data and objectives Show More ##### ## Agentic AI - Analytics Platforms (7) Autonomous Task Execution Capability to perform complex tasks without constant human input Multi-step Planning Ability to break down and plan multi-step processes Cross-system Integration Works across multiple software systems or databases Adaptive Learning Improves performance based on feedback and experience Natural Language Interaction Engages in human-like conversation for task delegation Proactive Assistance Anticipates needs and offers suggestions without prompting Decision Making Makes informed choices based on available data and objectives Show More ##### ## Agentic AI - Data Science and Machine Learning Platforms (7) Autonomous Task Execution Capability to perform complex tasks without constant human input Multi-step Planning Ability to break down and plan multi-step processes Cross-system Integration Works across multiple software systems or databases Adaptive Learning Improves performance based on feedback and experience Natural Language Interaction Engages in human-like conversation for task delegation Proactive Assistance Anticipates needs and offers suggestions without prompting Decision Making Makes informed choices based on available data and objectives Show More ##### ## Deployment & Integration - Analytics Platforms (4) No-code Dashboard Builder Enables non-technical users to build dashboards through intuitive, drag-and-drop interfaces Report Scheduling and Automation Enables automated report generation and scheduled delivery to stakeholders Embedded Analytics and White-labeling Allows dashboards and analytics to be embedded into external apps with branding flexibility Data Source Connectivity Supports integration with major data sources like cloud data warehouses, SQL/NoSQL databases, and SaaS applications Show More ##### ## Performance & Scalability - Analytics Platforms (2) Large data handling and Query Speed Efficiently processes large datasets with minimal lag and ensures high performance under load Concurrent User Support Maintains performance and uptime during high traffic from multiple users or teams Show More ##### ## Advanced Analytics & Modeling - Analytics Platforms (3) Data Modeling and Governance Supports semantic data layers, role-based access controls, and metadata governance Notebook and Script Integration Integrates with Jupyter, Python, or R for custom analytics and modeling Built-in Predictive and Statistical Models Provides native tools for statistical analysis, forecasting, and trend prediction Show More ##### ## Agentic AI Capabilities - Analytics Platforms (4) Auto-generated Insights and Narratives Uses AI to generate textual summaries, key takeaways, and data stories from dashboards Natural Language Queries Allows users to query data and build reports using conversational or plain language Proactive KPI Monitoring and Alerts Detects and notifies users about KPI anomalies or significant metric changes in real time AI Agents for Analytical Follow-ups Recommends next questions, analyses, or exploration paths using autonomous AI agents Show More ##### ## Personalized Intelligence - Analytics Platforms (3) Behavioral Learning for Contextual Query Refinement Learns from historical user interactions to improve and personalize query results over time Role-based Insight Personalization Tailors dashboard views and suggestions based on user roles, access levels, and past behavior Conversational and Prompt-based Analytics Supports AI-driven exploration via prompts or multi-turn conversations for iterative querying Show More ## Top-Rated Alternatives [ ![Databricks](https://images.g2crowd.com/uploads/product/hd_favicon/135d1c9e39e19ef56dc8d0bf90fce20f/databricks.svg "Databricks") Databricks 4.6/5 (1,283) ](https://www.g2.com/products/databricks/reviews) [ ![Snowflake](https://images.g2crowd.com/uploads/product/hd_favicon/1544409170/snowflake.svg "Snowflake") Snowflake 4.5/5 (707) ](https://www.g2.com/products/snowflake/reviews) [ ![Teradata Autonomous Knowledge Platform](https://images.g2crowd.com/uploads/product/hd_favicon/18effe7340087cf76270e479644d3e42/teradata-autonomous-knowledge-platform.svg "Teradata Autonomous Knowledge Platform") Teradata Autonomous Knowledge Platform 4.3/5 (355) ](https://www.g2.com/products/teradata-autonomous-knowledge-platform/reviews) [ View All Alternatives ](https://www.g2.com/products/cloudera/competitors/alternatives) ## Technology Glossary Features View full feature definition View definitions of the features and discover new technology terms. [View Glossary](/glossary) [Data Modeling](/glossary/data-modeling-definition) Data modeling is the process of creating visual representations of information systems to better communicate the connections between data points and structures. Learn more about data modeling in this G2 guide. [Data Manipulation](/glossary/data-manipulation-definition) Data manipulation is the process of organizing, modifying, and transforming data to improve accuracy, usability, and analysis across systems and workflows. 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