Build robust, scalable database platforms using the best open source technologies. From PostgreSQL and MongoDB to Redis and Elasticsearch, we provide comprehensive solutions for modern data architecture needs.
Explore Database SolutionsWorld's most advanced open source relational database with enterprise-grade features
Key Features:
Common Use Cases:
Performance:
10,000+ TPS
Scalability:
Petabyte scale
Flexible NoSQL document database for modern applications and agile development
Key Features:
Common Use Cases:
Performance:
1M+ ops/sec
Scalability:
Auto-scaling clusters
In-memory data structure store for caching, session management, and real-time analytics
Key Features:
Common Use Cases:
Performance:
1M+ ops/sec
Scalability:
Linear scaling
Distributed search and analytics engine for all types of data including textual and numerical
Key Features:
Common Use Cases:
Performance:
Billions of docs
Scalability:
Horizontal scaling
Database per service pattern with event-driven synchronization
Components:
Key Benefits:
Complexity:
High
Best For:
Large enterprise applications
Using different database technologies for different data storage needs
Components:
Key Benefits:
Complexity:
Medium
Best For:
Data-intensive applications
Storing all changes as a sequence of events with projection views
Components:
Key Benefits:
Complexity:
High
Best For:
Financial and audit systems
Separate models for reading and writing data with optimized stores
Components:
Key Benefits:
Complexity:
Medium
Best For:
High-read applications
Complete guide for setting up PostgreSQL with streaming replication and failover
Topics Covered:
Tools Required:
Time Required:
4-6 hours
Skill Level:
Intermediate
Building horizontally scalable MongoDB clusters for high-volume applications
Topics Covered:
Tools Required:
Time Required:
6-8 hours
Skill Level:
Advanced
Implementing Redis high availability and horizontal scaling patterns
Topics Covered:
Tools Required:
Time Required:
3-4 hours
Skill Level:
Intermediate
Production-ready Elasticsearch cluster with security and monitoring
Topics Covered:
Tools Required:
Time Required:
5-7 hours
Skill Level:
Advanced
OLTP Mixed
Throughput:
45,000 TPS
Latency:
2.1ms p95
Configuration:
32 vCPU, 128GB RAM
Optimized for mixed read/write workload
Document Inserts
Throughput:
150,000 ops/sec
Latency:
0.8ms p95
Configuration:
24 vCPU, 96GB RAM
Bulk inserts with write concern w:1
GET/SET Operations
Throughput:
1,200,000 ops/sec
Latency:
0.1ms p95
Configuration:
16 vCPU, 64GB RAM
In-memory operations, pipelining enabled
Log Ingestion
Throughput:
200,000 docs/sec
Latency:
50ms p95
Configuration:
3-node cluster, 32GB heap
Bulk indexing with refresh interval 30s
Complete cutover during maintenance window
Pros:
Cons:
Best For:
Small to medium databases
Downtime:
2-8 hours
Parallel environment with traffic switching
Pros:
Cons:
Best For:
Mission-critical systems
Downtime:
< 1 minute
Gradual migration of data and functionality
Pros:
Cons:
Best For:
Large enterprise systems
Downtime:
Near zero
Real-time sync with gradual traffic migration
Pros:
Cons:
Best For:
High-availability systems
Downtime:
< 5 minutes
Get expert guidance on database architecture, implementation, and optimization. Our team has deployed 500+ database solutions across various industries and scales.
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