Dremio Features

Aligns processing and distribution workflows on top of Apache Hadoop

Aligns processing and distribution workflows on top of Apache Hadoop

Facilitates solution to run on and scale to a large number of machines and systems

Curates collected data for big data analytics solutions to analyze, manipulate, and model

Aligns processing and distribution workflows on top of Apache Hadoop

Moves big data collection and processing to the cloud

Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems

Allows user to query data through query languages like SQL.

View and track pertinent metrics to find patterns and gain insights from data

Predict future data based on historical data sets

Interact with data visualization elements, such as charts and graphs, to drill down into data

Aligns processing and distribution workflows on top of Apache Hadoop

Integrates data from multiple external databases.

Facilitates the dissemination of collected big data throughout parallel computing clusters.

Receive data and information in real time

Import, collect, and capture data from multiple sources

Review data from past periods to reveal recurring tendencies and predict future performance

Provides varying estimates based on different scenarios

Apply statistical/mathematical models to sets of data

Merge data from multiple sources to a single data set

Set up connections to third-party platforms to improve business processes

Processes data and represents interpretations in a variety of graphic formats.

Strings together specific functions and datasets to automate analytics iterations.

Isolates certain datasets and facilitates management of data access.

Allows big data tool to run and record data within external applications.

Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations

Discover and connect variety of data sources to the application for analysis

Consolidates, Cleanses and Normalizes data from multiple disparate sources.

Helps save storage capacity and improves query performance.

Eliminates data inconsistency and duplications ensuring data integrity.

SQL based analytics functions like Time series, pattern matching, geospatial analytics etc.

Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS

Process of extracting and moving data from multiple sources to a single and unified database

Import, collect, and capture data from multiple sources

Analyze and gain insights into data in real-time

View and track pertinent metrics to find patterns and gain insights from data

Provides movement of data from one location to another.

Provides an overall strategy for data governance.

Integrates with BI Tools to transform data into Actionable Insights.

Provides speed in data processing and capturing unstructured, semi-structured and streaming data.

Provides On-Premise deployment options.

Provides Cloud deployment options (private or public cloud, hybrid cloud).

Manages huge volumes of data, upscale or downscale as per demand.

Policies, procedures and standards to manage and access data.

Provides specialization in data-driven insights by direct access to data analysts or end users.

Provides data in structured and readable formats.

Aids in establishing a data fabric with a network of various tools to operationalize data.

Provides users with options of architecture such as centralized or decentralized.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Use AI to generate content in the form of text, images, videos, etc.

Supports deployment across multiple environments or cloud platforms with consistent configuration management

Provides APIs and SDKs for seamless integration with orchestration, governance, and custom data tools

Allows querying and joining data across multiple warehouses and lakes without requiring data replication

Automatically adapts to schema or metadata changes in connected data sources while maintaining consistency

Enables users to create derived or calculated metrics based on governed data definitions

Provides built-in support for time-based calculations such as YoY, MoM, and rolling averages

Enhances performance by using intelligent caching, precomputation, and acceleration techniques

Automatically tunes and optimizes queries based on data size, frequency, and usage patterns

Provides visibility and control over how AI systems or automated agents interact with the semantic layer

Tracks how governed metrics and datasets are used in AI/ML training to ensure transparency, compliance, and clear data traceability

Provides version control for semantic models and metrics, with change tracking, rollback, and impact analysis to see how updates affect downstream data or reports

Allows users or AI assistants to explore and query metrics through natural language prompts

Enables AI and machine learning systems to directly consume standardized, governed metrics and logic

Suggests relevant metrics, joins, or insights based on context and historical usage patterns

Enables autonomous AI agents to compose, execute, and refine analytical queries via the semantic layer

Provides semantic context graphs that help AI agents understand data relationships and business logic

Allows semantic agents to trigger automated actions such as data refreshes, alerts, or report generation

Running multiple processors to handle separate parts of an overall task and manage complex tasks/computations.

Allows users to manage data from a number of sources

Application programming interface that allows for integration with other systems/databases

Blending and analysis of large data sets without moving data out of a database.

Observe and track the demand, usage, progress or quality of a system, product, or user

Active reporting of data and metrics

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

Active monitoring of systems, applications, or networks

Connect to big data sources

A set of indicators that tracks the performance of networks, applications, systems, teams, etc.

Generate one-off reports that meet information requirements

Alerts or notifications of various types such as pop-up messages, sounds, banners, or badges

Define levels of authorization for access to specific files or systems

Assemble applications and processes by dragging over and arranging pre-built components

Graphical representation of data

Import and export data to and from software applications

Looking at data from different sources and finding possible duplicates, or identical matches

Translate EDI formats into data suitable for use with company applications.

Securely stores data to prevent data loss or breaches

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Alter the layout and content of reports

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Move from one database to another, or upgrade the version of database software being used

Track the management and flow of data throughout the organization

Central repositories of integrated data from various sources

Assemble applications and processes by dragging over and arranging pre-built components

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Connect to big data sources

Generate one-off reports that meet information requirements

Alter the layout and content of reports

System alerts about the need to escalate an issue or request

Sample files or documents that could be customized as needed or used as is

Form predictions based on past and present data/trends

Move from one database to another, or upgrade the version of database software being used

Translate EDI formats into data suitable for use with company applications.

Define levels of authorization for access to specific files or systems

Application programming interface that allows for integration with other systems/databases

Removes data that is incomplete, inaccurate, or irrelevant from a dataset

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Creation and customization of dashboards

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Protect sensitive data for digital privacy

Security protocol that ensures secure, encrypted communication over the internet, safeguarding sensitive data from unauthorized access

Provides a channel for team members to share media files, communicate, and work together

Drag and drop/visual interfaces that allow non-tech users to build without writing code

Process and analyze large volume of data

Supports common databases such as MySQL and Oracle

Search and filter data across systems to locate required information by entering keywords or certain criteria

Use AI to generate content in the form of text, images, videos, etc.