Redis Software Features

Stores data as key-value pairs where key is a unique identifier.

Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc.

Stores and queries data as JSON-like documents.

Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc.

Allows users to index at ingest and query endlessly across data.

Notifies specific events like document inserts, updates, replaces, deletes etc and responds in real-time.

Designed to store interconnected data consisting of nodes and edges.

Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc.

Allows users to index at ingest and query endlessly across data.

Notifies specific events like document inserts, updates, replaces, deletes etc and responds in real-time.

Powerful query language that allows users to access patterns like traversals, JOINs, search, geospatial etc.

Implements auto horizontal data partitioning that allows storing data on more than one node to scale out.

Restores a database to a correct (consistent) state in the event of a failure.

Copy data across multiple servers through master-slave, peer-to-peer replication architecture etc.

Implements auto horizontal data partitioning that allows storing data on more than one node to scale out.

Restores a database to a correct(consistent) state in the event of a failure.

Copy data across multiple servers through master-slave, peer-to-peer replication architecture etc.

Create backups and provide methods to recover deleted/lost data

Receive data and information in real time

Implements auto horizontal data partitioning that allows storing data on more than one node to scale out.

Restores a database to a correct(consistent) state in the event of a failure.

Stores frequently-used data in system memory quickly.

Provides predefined system roles, privileges, and user-defined roles to users.

Provides an audit log to track access and operations performed on databases for regulatory compliance.

Provides encryption capability for all the data at rest using encryption keys.

Provides predefined system roles, privileges, and user-defined roles to users.

Allows integration with external security mechanisms like Kerberos, LDAP authentication etc.

Provides an audit log to track access and operations performed on databases for regulatory compliance.

Provides encryption capability for all the data at rest using encryption keys.

Provides predefined system roles, privileges, and user-defined roles to users.

Allows integration with external security mechanisms like Kerberos, LDAP authentication etc.

Provides an audit log to track access and operations performed on databases for regulatory compliance.

Provides encryption capability for all the data at rest using encryption keys.

Available on multiple operating systems like Linux, Windows, MacOS etc.

Provides support to handle structured, semi-structured, and unstructured data with equal effect.

Available on multiple operating systems like Linux, Windows, MacOS etc.

Allows users to connect business intelligence tools to the database.

Connect to big data sources

Provides support to handle structured, semi-structured, and unstructured data with equal effect.

Allows users to connect business intelligence tools to the database.

Available on multiple operating systems like Linux, Windows, MacOS etc.

Helps interpret SQL queries and determine the fastest method of execution

One-off queries made on an as-needed basis

Helps interpret SQL queries and determine the fastest method of execution

Allows semantic search service by organizing data.

Allows indexing of data for search and retrieval.

The feature aids in filtering queries by metadata thus achieving accurate search.

This feature integrates vectors and metadata indexes into a single index.

Orchestrates retrieval, reranking, and enrichment steps within RAG workflows

Optimizes chunk selection, context assembly, and grounding specifically for LLM consumption

Enables advanced tuning of lexical, semantic, and reranked retrieval strategies

Provides insights into query behavior, retrieval quality, and relevance performance

Ensures resilience through redundancy, failover, and recovery mechanisms

Manages embedding updates, re-indexing, and model version changes over time

Enables semantic search across text, images, audio, or video using embeddings

Allows teams to bring their own embedding models or LLM providers and change them without re-architecting

Supports near-real-time index updates as source data changes

Enriches content using chunking, metadata inference, entity extraction, or OCR during indexing

Enforces document-, field-, or metadata-level permissions during retrieval

Supports regional data controls, retention rules, and regulatory compliance

Tracks queries, retrieved content, and access decisions for compliance and debugging

Enables fine-grained control over ranking using rules, weights, feedback loops, or learning-to-rank models

Improves retrieval quality through query rewriting, semantic expansion, or intent detection

Supports multi-step retrieval pipelines where initial candidates are reranked using ML or LLM-based approaches

Adjusts retrieval and ranking based on user context, behavior, or application-level signals

Transformation of data from one format to another

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

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

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

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

Data is backed up automatically to prevent data loss

Active monitoring of systems, applications, or networks

Plan, schedule, and execute organization's accounts and assets to ensure compliance with policies and laws

Graphical representation of data

Generate one-off reports that meet information requirements

Track and manage adherence to policies for any service, product, process, or supplier

Compile and organize data into specific metrics

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

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

Process of checking different types of data for accuracy to avoid errors or inconsistencies

Allows developers to check if their applications/web browsers are running as expected.

Import, collect, and capture data from multiple sources

Systematic evaluation of the security of a company's overall security system and situation

Define levels of authorization for access to specific files or systems

Set & manage permission levels based on user roles and restrict access to only authorized individuals

Track the management and flow of data throughout the organization

Search and find data in a structured format

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

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

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

Identify component attributes like servers, hardware, software, and manage relationships across all services

A record of all activities within the system, including user access, changes made, etc.

Specific for use in NoSQL Databases

Import and export data to and from software applications

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

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

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

Compatible with serverless backends

Allows users to manage data from a number of sources