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Database & Caching

Data Systems That Stay
Fast Under Pressure.

Relational and NoSQL databases, in-memory caching, and event streaming engineered for consistency, scale, and complex enterprise reporting - with AI-assisted query and cache optimisation.

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DATA PostgreSQL MongoDB Redis Kafka GridGain
What we deliver

Database & Caching we work with.

Relational Databases
PostgreSQL, MySQL, and SQL Server architecture tuned for consistency and complex reporting.
PostgreSQLMySQL
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NoSQL & Document Stores
MongoDB and other NoSQL systems for flexible, high-throughput data models.
MongoDBNoSQL
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Caching (Redis / GridGain)
In-memory caching architectures that keep high-traffic platforms fast under load.
RedisGridGain
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Event Streaming (Kafka)
Event-driven messaging and queue architectures for reliable, asynchronous processing at scale.
KafkaEvent-Driven
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What's included

Database & Caching.

✔Relational database architecture and schema design
✔NoSQL data modelling for high-throughput workloads
✔Redis / GridGain caching strategy and implementation
✔Kafka-based event streaming and queue architecture
✔AI-assisted query optimisation and slow-query detection
Our stack
PostgreSQL MySQL MongoDB Redis GridGain Apache Kafka SQL Server
Why choose OKRUTI

Engineering depth, not just a tech list.

Consistency at enterprise scale
In-memory performance engineering
Event-driven data architecture
AI-assisted query tuning
Proven under high transaction volume
FAQ

Common questions about database & caching.

Which databases do you specialise in?
PostgreSQL and MySQL for relational workloads, MongoDB for document/NoSQL needs, and SQL Server where Microsoft-centric stacks require it.
How do you decide between SQL and NoSQL for a project?
We look at your data's consistency requirements, query patterns, and scale needs rather than defaulting to one model - many platforms end up using both.
What caching strategy do you recommend for high-traffic platforms?
Typically Redis or GridGain in-memory caching in front of the primary database, tuned to your read/write ratio and invalidation requirements.
Do you support event streaming architectures like Kafka?
Yes. We design Kafka-based event streaming for asynchronous processing, audit trails, and decoupling services at scale.
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Free 1-hour technical consultation. No fluff, just architecture.

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