Elasticsearch & Redis
search and caching layer
Elasticsearch powers our full-text search and analytics. Redis handles caching, sessions, and real-time data. Together they make applications fast.
Full-text
search
Real-time
caching
Sub-second
response times
ISO 27001
certified operations
What is
Elasticsearch & Redis
Elasticsearch and Redis are key complementary we useds in the Cognito Works stack. Elasticsearch provides full-text search and analytics, Redis handles caching, sessions, and real-time data processing.
Why
Elasticsearch & Redis
Fast search, caching, session management, and real-time analytics. Four reasons why these we useds are essential in our stack.
Full-text search
Elasticsearch indexes millions of documents and returns results in milliseconds. Autocomplete, fuzzy matching, faceted search, relevance tuning.
In-memory caching
Redis keeps frequently used data in memory. Database response times drop from tens of milliseconds to single-digit microseconds.
Session and queue management
Redis as session store for stateless applications and message broker for asynchronous processing.
Real-time analytics
Elasticsearch aggregations for dashboards, log analysis, and business intelligence. Sub-second queries over billions of events.
Key features
Elasticsearch a Redis
E-commerce search
Product catalog with facets, filters, autocomplete, and relevance scoring. Customers find what they need in milliseconds.
Full-text search
Search across documents, articles, FAQs, product descriptions. Czech language support, lemmatization, fuzzy matching.
Database query caching
Redis caches results of frequent queries. Reduces PostgreSQL load and accelerates response times by orders of magnitude.
Session management
Redis as central session store. Stateless applications scalable horizontally without sticky sessions.
Logging & monitoring
Elasticsearch as log storage. Kibana for visualization, anomaly alerting, fast troubleshooting across all services.
Asynchronous processing
Redis as message broker for job queues. Emails, notifications, PDF generation, data imports without blocking the main thread.
Where we deploy
Elasticsearch & Redis
E-commerce platforms
Marco 3.0. Product catalog with facets, filters, autocomplete. Sub-second search across thousands of products.
Content platforms
Sulu CMS portals. Full-text search across articles, pages, and documents with Czech morphology support.
B2B portals
Smith A. Product search, order history, partner documentation. Fast access to frequently used data.
AI applications
Elasticsearch for semantic search and RAG pipelines. Redis for model response caching and session management.
Content platforms
Sulu CMS. Full-text search across articles, pages, documents. Autocomplete and faceted navigation.
API services
Redis for rate limiting, queue management, and API response caching. Elasticsearch for log aggregation and monitoring.
Frequently asked questions
For simple exact-match queries, PostgreSQL is enough. For full-text search with facets, autocomplete, and relevance scoring, Elasticsearch is the right choice.
We use event-driven synchronization. When data changes in PostgreSQL, events trigger Elasticsearch index updates. This ensures search results are always current without impacting database performance.
Redis supports AOF and RDB persistence. For critical data, we use PostgreSQL as the source of truth and Redis as the speed layer.
Yes. We design the index schema, set up the cluster, build the search API, and tune relevance. Drop-in or custom integration.
We follow Elasticsearch release cycles, test upgrades in staging, and deploy with zero downtime. Index schema migrations are automated.
