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Feature Engineering & Indicators · Reviewed 27 Oct 2026

Redis

Fast in-memory database for caching, vector search, and NoSQL.

from $200 · free tier · redis.io ↗

Paid against free › Feature Engineering & Indicators › Redis

Redis at a glance
734.7KEstimated total trafficModeled monthly visits22.1KRanking keywordsPublic search sample97/100Technical health15 pages checked0Referring domainsLive backlink summary

Overview

01

Summary

The useful answer before the supporting detail.

Redis is a fast in-memory database used for caching, vector search, and NoSQL workloads S1. It serves developers and enterprises needing low-latency data access for applications like real-time analytics, AI, and session management S1. Redis offers a fully managed cloud service, on-premises software, and an open-source framework, with a feature store for real-time ML pipelines S1 S39.

02

Product identity and positioning

Name, category, positioning, audience, and first-party claims.

  • Identity: Redis is an in-memory database and feature store provider S1 S39.
  • Core purpose: Solves the problem of slow data access by keeping datasets in memory for sub-millisecond reads and writes S1.
  • Intended users: Developers and enterprises building fast, scalable applications S1.
  • Product scope: Includes Redis Cloud (managed), Redis Software (on-prem), and an open-source framework S1.
  • Positioning: Positioned as the world's fastest in-memory database S1.
  • Claimed distinction: Claims top performance through in-memory dataset operation S1.
03

Use cases and audiences

Who the product serves and the jobs it is designed to handle.

AudiencePractical use case
DevelopersBuild fast applications with caching and real-time data access S1.
AI/ML teamsServe features instantly for fraud detection, recommendations, and real-time decisioning S39.
EnterprisesDeploy fully managed, production-ready apps on Google Cloud, Azure, and AWS S48.
Gaming companiesCache high volumes of game data to support player activity during events S93.

Features

09

Features and capabilities

Core functions and evidence-backed product capabilities.

CapabilityWhat it does
Data structuresSupports strings, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, geospatial indexes, and streams S1.
CachingProvides sub-millisecond read/write at scale for caching workloads S1.
Vector searchEnables semantic search and RAG applications S1.
Real-time messagingSupports event-driven messaging and data pipelines via streams S1.
Feature storeOrchestrates offline data systems and real-time serving for ML features S39.
Redis Data IntegrationProvides CDC across structured data for near-real-time sync S1 S41.
Redis InsightUI to visualize, query, and debug Redis data S1.
10

Integrations and ecosystem

Connected products, exports, APIs, and workflow compatibility.

Integration or interfaceTypeWhat it enables
Snowflake, Databricks, Spark, PostgresIntegrationIntegrate with offline data systems for feature store pipelines S39.
FeastIntegrationUse Feast as offline store and Redis for real-time online serving S39.
Datadog, Dynatrace, New RelicIntegrationMonitor Redis Cloud with third-party tools S15.
GrafanaIntegrationVisualize Redis metrics in dashboards S49.
ODBC/JDBC connectorIntegrationConnect to Redis from BI tools S49.
Spark connectorIntegrationProcess Redis data with Apache Spark S49.
LDAPIntegrationIntegrate with LDAP for authentication S49.

Pricing

11

Pricing and plans

Published plans, free access, trials, credits, and pricing limitations.

Plan or offerVerified price and billingIncludedLimits
Redis Cloud Free$0 S41Single database S4130 MB S41
Redis Cloud EssentialsFrom $0.007/hour S41Single database S41250 MB to 100 GB S41
Redis Cloud ProFrom $0.014/hour, minimum $200/month S41Dedicated deployment, multiple databases S41Not established
Feature FormContact sales S39Not establishedNot established

Competition

12

Competitive landscape

Domains competing for the same organic search demand.

Sampled competitors

CompetitorFirst-page appearancesSampled queriesAverage positionQueries observed
percentagecal.com313.37.8 6
appbrain.com1127.8 6
medium.com112aof redis
wccftech.com1137.8 6
stackoverflow.com114aof redis
docs.cloud.google.com115aof redis
php.net1167.8 6
reddit.com1177.8 6
learn.microsoft.com117aof redis
math.answers.com1187.8 6

Website intelligence — Collected evidence

Customers, testimonials, and first-party review claims

No supporting public-page evidence was collected for this category.

Independent review sources discovered

PlatformStatusDiscovered source
Googlediscovered_not_scrapedhttps://drive.google.com/file/d/1ocJNDbEUxXVJqyBVD35k-Vvr1y8hjN5k/view
Googlediscovered_not_scrapedhttps://groups.google.com/g/feast-dev/c/D0IHN_DALFA?pli=1
Googlediscovered_not_scrapedhttps://drive.google.com/file/d/1KfOMI9C-aitJNPdGB56L-6tA8BBp9gsl/view
13

AI visibility

Measured ChatGPT and Google AI mentions with cited sources.

AI-assistant referral traffic

  • Estimated current generative-AI referral share: 2.0%
MonthSource
—All AI assistants
—All AI assistants
—All AI assistants

Website intelligence — Collected evidence

Site-stated AI capabilities

Page typeEvidenceSource
featuresFraud detectionStop fraud, protect customersReal-time decisionsAct on data in real timeCaching & performanceOur bread & butter Real-time messagingStreams at the speed of thoughtSession managementConsistent experiences everywhereLeaderboardsKnow who’s winninghttps://redis.io/feature-form/
featuresMachine learning thrives on real-time data, but creating real-time pipelines can seem impossible. Not with Feature Form. Simply define your features as code, and Feature Form will turn them into prod-grade data pipelines for model training and inference.https://redis.io/feature-form/
featuresOperationalize real-time data for machine learninghttps://redis.io/feature-form/
featuresBuilt for enterprise AI teamshttps://redis.io/feature-form/
featuresFraud detectionStop fraud, protect customersReal-time decisionsAct on data in real timeCaching & performanceOur bread & butter Real-time messagingStreams at the speed of thoughtSession managementConsistent experiences everywhereLeaderboardsKnow who’s winninghttps://redis.io/solutions/
featuresFraud detectionStop fraud, protect customersReal-time decisionsAct on data in real timeCaching & performanceOur bread & butter Real-time messagingStreams at the speed of thoughtSession managementConsistent experiences everywhereLeaderboardsKnow who’s winninghttps://redis.io/blog/building-feature-stores-with-redis-introduction-to-feast-with-redis/
featuresA feature store is a centralized place where data scientists from different teams across your organization can share features) for machine learning. The feature store allows them to search, reuse, and serve features in production at scale. As MLOps matures, feature stores are becoming a cornerstone of machine learning platforms for a few reasons:https://redis.io/blog/building-feature-stores-with-redis-introduction-to-feast-with-redis/
featuresWhen companies need to deliver real-time, ML-based applications to support high volumes of online traffic, Redis is most often selected as the foundation for the online feature store, thanks to its ability to deliver ultra-low latency with high throughput at scale. We’re seeing ML cloud platform providers offer feature stores using Redis, as in the recent examples of H2O AI Feature Store and Microsoft’s Azure Feature Store. And we’re also seeing a host of build-your-own implementations of feature stores using Redis at a variety of companies including Wix, Swiggy, Comcast, Zomato, AT&T, DoorDash, iFood, and Uber.https://redis.io/blog/building-feature-stores-with-redis-introduction-to-feast-with-redis/
featuresOpen source feature store implementations such as Feast are also choosing Redis. Redis was selected as Feast’s online store for real-time use cases at scale, first by the Indonesian ride-hailing company Gojek (who was the initial creator of Feast in collaboration with Google), and later by Feast’s early adopters, such as Udaan and Robinhood. In addition to that, Redis was selected by Microsoft for the online store of its new Azure Feature Store with Feast (stay tuned for more details on that soon!).https://redis.io/blog/building-feature-stores-with-redis-introduction-to-feast-with-redis/
featuresFeast (Feature store) is an open source feature store that’s part ofthe Linux Foundation’s AI & Data Foundation. Feast can serve features from a low-latency online store or from an offline store, while also providing a central registry, storage, and serving. This allows ML engineers and data scientists to discover the relevant features for ML use cases and serve them in production.https://redis.io/blog/building-feature-stores-with-redis-introduction-to-feast-with-redis/
featuresFraud detectionStop fraud, protect customersReal-time decisionsAct on data in real timeCaching & performanceOur bread & butter Real-time messagingStreams at the speed of thoughtSession managementConsistent experiences everywhereLeaderboardsKnow who’s winninghttps://redis.io/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/
featuresFeature Stores for Real-time AI/ML: Benchmarks, Architectures, and Case Studieshttps://redis.io/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/
features[](https://claude.ai/new?q=Search%20the%20web%20and%20answer%3A%20Summarize%20this%20Redis%20blog%20post%3A%20%22Feature%20Stores%20for%20Real-time%20AI%2FML%3A%20Benchmarks%2C%20Architectures%2C%20and%20Case%20Studies%22%20%E2%80%94%20https%3A%2F%2Fredis.io%2Fblog%2Ffeature-stores-for-real-time-artificial-intelligence-and-machine-learning.md)https://redis.io/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/
features[](https://www.perplexity.ai/search/new?q=Summarize%20this%20Redis%20blog%20post%3A%20%22Feature%20Stores%20for%20Real-time%20AI%2FML%3A%20Benchmarks%2C%20Architectures%2C%20and%20Case%20Studies%22%20%E2%80%94%20https%3A%2F%2Fredis.io%2Fblog%2Ffeature-stores-for-real-time-artificial-intelligence-and-machine-learning.md)https://redis.io/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/
featuresReal-time artificial intelligence / machine learning (AI/ML) use cases, such as fraud prevention and recommendation, are on the rise, and feature stores play a key role in deploying them successfully to production. According to popular open source feature store Feast, one of the most common questions users ask in their community Slack is: howscalable/performantis Feast?This is because the most important characteristic of a feature store for real-time AI/ML is the feature serving speed from the online store to the ML model for online predictions or scoring. Successful feature stores can meet stringent latency requirements (measured in milliseconds), consistently (think p99) and at scale (up to millions of queries per second, with gigabytes to terabytes-sized datasets) while at the same time maintaining a low total cost of ownership and high accuracy.https://redis.io/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/
featuresAs we will see in this post, the choice of an online feature store, as well as the architecture of the feature store, play important roles in determining how performant and cost-effective it is. It’s no wonder that oftentimes companies, before choosing their online feature store, perform thorough benchmarking to see which choice of architecture or online feature store is the most performant and cost-effective. In this post, we will review architectures and benchmarks from both DIY feature stores built by companies successfully deploying real-time AI/ML use cases and open source and commercial feature stores. Let’s begin.https://redis.io/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/
featuresIn the diagram above you can see an example of how the online mortgage company Better.com implemented its lead scoring ranking system using the open-source Feast feature store. As presented by Vitaly Sergey, Senior Software Engineer at Better.com, the features are materialized from the offline stores (S3, Snowflake, and Redshift) to the online store (Redis). In addition to that, features are also ingested into the online store from streaming sources (Kafka topics). Feast recently added support for streaming data sources (in addition to batch data sources) which is currently supported only for Redis. Supporting streaming data sources is very important for real-time AI/ML use cases as these use cases rely on fresh live data.https://redis.io/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/
featuresFraud detectionStop fraud, protect customersReal-time decisionsAct on data in real timeCaching & performanceOur bread & butter Real-time messagingStreams at the speed of thoughtSession managementConsistent experiences everywhereLeaderboardsKnow who’s winninghttps://redis.io/blog/introducing-redis-feature-form/
featuresFraud detectionStop fraud, protect customersReal-time decisionsAct on data in real timeCaching & performanceOur bread & butter Real-time messagingStreams at the speed of thoughtSession managementConsistent experiences everywhereLeaderboardsKnow who’s winninghttps://redis.io/solutions/ai-cost-optimization/
featuresAI & ML Appshttps://redis.io/feature-form/

These are first-party product claims, not independent measurements of AI-search visibility.

14

Marketing opportunities

Actions calculated directly from the collected evidence.

OpportunityRecommended actionEvidence
Competitor gapReview the sampled queries where percentagecal.com appears.3 first-page appearances across 7.8 6

Website intelligence — Collected evidence

Website evidence gaps

  • customers: no usable public page was collected; verify whether the site publishes this evidence.
  • reviews: no usable public page was collected; verify whether the site publishes this evidence.
  • changes: no usable public page was collected; verify whether the site publishes this evidence.
  • identity: no usable public page was collected; verify whether the site publishes this evidence.
  • technical: no usable public page was collected; verify whether the site publishes this evidence.

Trust and proof

15

Customers, proof, and reviews

Published proof, customer signals, and review evidence.

Independent reviews

PlatformPageHow it was foundNote
CheckThatRedis Reviews 2026: What Enterprise Users Really SayGrounded web searchThis roundup synthesizes verified user reviews from TrustRadius (8.9/10 across 77 enterprise reviews), along with available data from G2, Capterra, and Gartner Peer Insights. The analysis covers aggregated ratings, praise and criticism patterns from verified users, operational challenges to expect, and how Redis compares to Memcached, Hazelcast, and DragonflyDB, with important caveats about data availability and the operational maturity required for successful deployments. ... On TrustRadius, Re
G2Redis Products / Read 172 Reviews on G2Grounded web search# Redis 4.5 out of 5 stars 5 star 69% 4 star 27% 3 star 2% 2 star 0% 1 star 0% 172 reviews - 6 categories - 3 profiles Average star rating 4.5 Serving customers since 2011 ... / Redis Software Its light weighted and easy to manange. Fast

Customer proof

Proof typeNamed customer or sourceEvidence
Case studyEtermaxcustomer case study — Redis Cloud was not only able to meet high availability and performance demands, it also helped cut Etermax’s AWS infrastructure costs by 30%. (Etermax - Redis)
Case studyNianticcustomer case study — To support heightened player activity, Niantic caches high volumes of game data in a Redis Enterprise cluster. (Optimizing Pokémon GO: How a Centralized Redis Cluster Improved Performance and Reliability During Popular Raid Events)

Independent mentions

  • You might not need Redis / Hacker News — use it, it actually slows things down. Using it, you're introducing network latency and serialization overhead. Sometimes that's worth it, especially if your database is falling over, but a lot of the time people use it and it just makes everything more
  • The Fastest Redis Ever / Hacker News — This sort of makes me sad. Redis has strayed from what its original goal/purpose was. I’ve been using it since it was in beta. Simple, clear, fast. The company ... for now keeps trying to add more and more functionality using Redis, that doesn’t belong
  • Procesio cut latency by 60% with Redis Cloud & unlocked real-time automation / Redis — 's scale, speed is a feature. By caching frequently accessed data, Redis Cloud slashed ... This raw performance is critical for enterprise use cases like e-transport, where goods must be registered with government systems in near real-time to avoid
  • MrQ scales personalized gaming experiences with Redis Cloud / Redis — At the same time, Redis minimized unnecessary interservice communication: game configurations and ... amazing performance of Redis as a distributed cache and the simplicity of use, you can do amazing things with it
  • Redis Stack / Hacker News — Redis Stack / Hacker News Redis Stack (redis.io) 158 points by hadrianpaulo on March 31, 2022 / hide / past / favorite / 69 comments ... much the direction of all specialty database providers (MongoDB, Redis) are moving into. Everyone wants to be able
  • TELUS’ Optik TV service gains greater reliability with Active-Active Redis — source, but ran into challenges managing and maintaining Redis availability for their mission-critical applications on Optik TV. TELUS ... application, TELUS saw significant benefits in resilience, reliability, and overall performance of the application

External links were grounded in one live web search. Search snippets are leads, not independently scraped page content; rejected links remain available in Review evidence.

16

Company, security, and trust

Ownership, policies, security signals, and public trust evidence.

SignalFindingSource
Company and ownershipMaintain full access control, auditability, and stay compliant without compromising speed. Security is part of the system.source
Contact and supportWe hope you’ve enjoyed this introduction to using Feast with Redis. We’ll be posting more resources soon, but if you have any feedback or questions, please don’t hesitate to contact us.source
Legal and privacyIn compliance with our Privacy Policy, Redis uses cookies to enhance your experience, provide personalized content, and analyze our traffic. By clicking "Accept", you consent to our use of cookies. To manage or opt-out,source
Security and complianceSecret providers, mTLS, encrypted transportsource
Uptime and status page• 99.999% uptime SLAsource
Domain registered2010-05-28—
Domain expires2027-05-28—

Every trust signal above is backed by a collected page or a registration record.

17

Documentation and product updates

Help resources, product guidance, and visible changes over time.

Resource or updateTypeWhat is availableDate or freshness
DocsDocumentationDocumentation is publicly available. (source)Not dated
Contact and supportSupportPublic contact and support channel. (source)Not dated
Contact and supportSupportPublic contact and support channel. (source)Not dated
What Is a Solution Architect, and How to Become One / RedisGuideDevelopers love Redis. Unlock the full potential of the Redis database with Redis Enterprise and start building blazing fast apps. (source)Not dated
About Redis: Fast in-memory databaseRelease notesPublic product change history. (source)Not dated
Redis pricing calculator: find your plan fastRoadmapPublic product roadmap. (source)Not dated

Not found in the collected public sources: status page, separate help center or knowledge base.

Technical

18

Technical and delivery signals

Delivery model, platforms, API, data ownership, reliability claims and release activity.

SignalFindingSource
Delivery model (cloud, self-hosted, desktop, browser extension)Offered as fully managed cloud, on-prem software, and open-source framework S1.S1
Platforms and appsWorks on Linux, *BSD, and Mac OS X S1.S1
API and extensibility (API, SDK, webhooks, MCP, plugins)Provides client libraries for Python, Node, Java, Go, .NET, and more S1.S1
Data ownership and exportNot published on the collected pages.—
Performance and reliability claimsClaims sub-millisecond read/write at scale S1.S1
Release activityNot published on the collected pages.—
19

Measured infrastructure

Domain, certificate, and hosting signals, measured directly.

SignalFinding
TLS certificateGoogle Trust Services, valid, expires 2026-12-03
Security headersHSTS, CSP
Headers not servedX-Content-Type-Options, X-Frame-Options, Referrer-Policy
Server headercloudflare
Mail handled byus-smtp-inbound-2.mimecast.com, us-smtp-inbound-1.mimecast.com
Nameserversns-1248.awsdns-28.org, ns-1731.awsdns-24.co.uk

Not measurable: wayback: rate limited by archive.org, ladder stopped after 1 probe(s); rdap: exceeded the overall budget; wayback: exceeded the overall budget; tls: exceeded the overall budget; dns: exceeded the overall budget; headers: exceeded the overall budget. A gap here means the lookup was unavailable, not that the finding is negative.

20

Technical site audit

A bounded multi-page crawl with page-level issues and URLs.

Scout — Bounded technical crawl

  • Pages crawled: 15 of 15 maximum
  • Technical health: 97/100
  • Critical issues: 0
  • Warnings: 6
  • Notices: 4

Issues

SeverityIssueValueAffected URL
noticeMeta description length should be reviewed173https://redis.io/langcache/
noticePage is marked noindex—https://redis.io/context-retriever/
noticeMeta description length should be reviewed47https://redis.io/feature-form/
noticeMeta description length should be reviewed336https://redis.io/resources/videos/agent-memory-workshop/
warningDuplicate meta description in audit sample6https://redis.io/
warningDuplicate meta description in audit sample6https://redis.io/resources/agent-memory-benchmark-report/
warningDuplicate meta description in audit sample6https://redis.io/iris/
warningDuplicate meta description in audit sample6https://redis.io/context-retriever/
warningDuplicate meta description in audit sample6https://redis.io/agent-memory/
warningDuplicate meta description in audit sample6https://redis.io/solutions/flex/

Crawled pages

StatusTitleH1sWordsResponseURL
200Redis - Real-time data for agents & apps11358226 mshttps://redis.io/
200Agent Memory benchmark report \Redis13077497 ms
200Redis Iris \Redis11896349 ms
200Redis LangCache11411194 mshttps://redis.io/langcache/
200Context Retriever \Redis11299211 ms
200Redis Agent Memory \Redis11293395 ms
200Redis Data Integration (RDI) — Real-time data, Redis fast11864317 mshttps://redis.io/data-integration/
200Flex \Redis11321368 ms
200Fast caching solutions with Redis11812569 mshttps://redis.io/solutions/caching/
200Fast messaging solutions with Redis11556527 mshttps://redis.io/solutions/messaging/
200Fast session management solutions with Redis12128480 mshttps://redis.io/solutions/session-management/
200Redis Search: real-time search & query at scale11360178 mshttps://redis.io/search/
200Redis Feature Store11640305 mshttps://redis.io/feature-form/
200Agent memory workshop11273337 mshttps://redis.io/resources/videos/agent-memory-workshop/
200Download Redis now and learn what fast really means12376470 mshttps://redis.io/downloads/

This is a bounded Scout crawl. Core Web Vitals and Lighthouse scores are not claimed unless a dedicated performance audit is connected.

21

Search Console and Analytics

First-party search and behavioral data connection state.

Modeled acquisition channels

ChannelEstimated share
direct32.9%
search49.1%
search organic48.4%
search paid0.7%
social4.6%
social organic4.3%
social paid0.3%
referrals9.9%
paid referrals0.4%
mail1.1%
gen ai2.0%
affiliate0.0%
other0.0%

First-party connections

IntegrationStatusData available after connection
Google Search ConsoleNot connectedClicks, impressions, CTR, average position, queries, pages, countries, and devices
Google AnalyticsNot connectedOrganic sessions, engagement, landing pages, conversions, geography, and devices

No first-party Search Console or Analytics numbers are shown until the site owner authorizes the corresponding Google account. Scout traffic model values above are modeled estimates, not private analytics totals.

Limits and method

22

Limitations and open questions

Known constraints and missing evidence from the collected pages.

The collected pages do not mention specific competitors. Evidence gaps include lack of detailed pricing for Feature Form, no explicit data export procedures, and no independent review ratings. Open questions remain about the full feature set of Redis Software and the specifics of the open-source licensing.

23

Sources, method, and limitations

Evidence inventory, collection method, provider use, and constraints.

This report is based on 15 collected pages from redis.io, including product, pricing, documentation, and blog pages. The evidence catalog includes 180 items, with sources ranging from official product pages to blog posts. External proof search was enabled but only one request was made, and no external review profiles were scraped. Limitations include potential bias from vendor-published content and lack of independent verification.

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