Distributed Apache Cassandra Management
Harness the power of planet-scale NoSQL. We manage massive distributed deployments so you can focus on data modeling. Specialized in multi-DC replication, linear scalability, and always-on availability.
Core Capabilities
Multi-DC Replication
Expert implementation of NetworkTopologyStrategy across multiple data centers. We configure tunable consistency levels (LOCAL_QUORUM, EACH_QUORUM) and automate repair operations for eventual consistency.
Linear Scalability
Add nodes dynamically without downtime. Cassandraβs masterless architecture eliminates single points of failure. We optimize token distribution and leverage virtual nodes (vnodes) for balanced data distribution.
Data Modeling
Query-driven data modeling with partition keys, clustering columns, and strategic denormalization. We design schemas optimized for read/write patterns, leveraging collections, UDTs, and materialized views.
Performance Tuning
Deep optimization of compaction strategies (STCS, LCS, TWCS), read/write path tuning, and memory management. We analyze SSTable distribution, optimize bloom filters, and configure compression ratios.
Methodology
Cluster Assessment & Design
Comprehensive analysis of your data access patterns, consistency requirements, and scale projections to architect the optimal ring topology.
- Data Model Review
- Capacity Planning
- Replication Strategy Design
Deployment & Migration
Cloud-native Kubernetes deployment using K8ssandra or traditional bare-metal setup. Zero-downtime migration from legacy systems using dual-write patterns and incremental backfill.
- Multi-DC Setup
- Data Migration Scripts
- SSTable Import/Export
Optimize & Monitor
24/7 monitoring using Prometheus + Grafana with custom Cassandra exporters. Automated repair scheduling via Cassandra Reaper and predictive alerting for node failures.
- JMX Metrics Collection
- Incremental Repair
- Query Pattern Analysis
Technical Specifications
| Feature | Standard Tier | Enterprise Tier |
|---|---|---|
| Cassandra Versions | 3.x, 4.0 | 3.x, 4.0, 4.1, 5.0 |
| Cluster Size | Up to 50 Nodes | 1000+ Nodes Multi-DC |
| Repair Management | Manual Repair | Cassandra Reaper Automation |
| Backup Solution | nodetool snapshot | Medusa + S3 Integration |
| Support SLA | 1 Hour Response | 15 Min Response |
Industry Success
Netflix-Scale Deployments
Architected 500-node global cluster handling 1M writes/sec for video metadata. Multi-region active-active with sub-5ms latency using LOCAL_QUORUM.
Sub-Millisecond Writes
Tuned time-series workload for trading signals achieving P99 latency under 800ΞΌs. Optimized TimeWindowCompactionStrategy with 15-minute windows.
1000+ Node Clusters
Managed planet-scale deployment across 5 continents with 1000+ nodes for subscriber data. Handled 10B+ daily transactions with 99.999% availability.
Ready to scale infinitely?
Schedule a free 30-minute technical discovery call with a Senior Cassandra Architect. No sales fluff, just engineering.
Advanced Cassandra Technologies
DataStax Enterprise
Commercial Cassandra distribution with advanced security, search, analytics, and graph capabilities plus enterprise support.
- β’ Advanced security features
- β’ Integrated Solr search
- β’ DataStax Studio tooling
Cassandra Reaper
Automated repair orchestration for managing anti-entropy repairs across massive clusters with scheduling and progress tracking.
- β’ Incremental repair scheduling
- β’ Repair progress monitoring
- β’ Cross-DC coordination
Change Data Capture
Real-time data streaming to Kafka, Pulsar, or event buses. Capture mutations with low latency for event-driven architectures.
- β’ CommitLog-based CDC
- β’ Kafka integration
- β’ Event streaming pipelines
Vector Search
Native vector search in Cassandra 5.0 for AI/ML embeddings. Store and query high-dimensional vectors for semantic search and RAG applications.
- β’ Vector data types (5.0+)
- β’ ANN similarity search
- β’ LLM embedding storage
Spark Integration
Analytics on Cassandra data using Spark Cassandra Connector. Run batch processing, aggregations, and ML directly on distributed data.
- β’ Spark Cassandra Connector
- β’ Batch analytics pipelines
- β’ DataFrames integration
Kubernetes Operator
Cloud-native deployment using K8ssandra operator for Cassandra on Kubernetes. Automated scaling, backups, and repair operations.
- β’ K8ssandra operator
- β’ Helm chart deployment
- β’ Auto-scaling policies
Comprehensive Service Tiers
Essential
For small to medium clusters
- βCassandra 3.x/4.x management
- βUp to 20 nodes single DC
- βnodetool snapshot backups
- βBasic JMX monitoring
- βManual repair scheduling
- βBusiness hours support
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MOST POPULAR
Professional
For production workloads
- βAll Essential features plus:
- βCassandra 3.x, 4.x, 5.0 support
- βMulti-DC replication (2-3 DCs)
- βCassandra Reaper automation
- βMedusa backup integration
- β24/7 Prometheus monitoring
- β1-hour response SLA
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Enterprise
Planet-scale deployments
- βAll Professional features plus:
- β1000+ node clusters
- β5+ data center replication
- βK8ssandra/Kubernetes deployment
- βDataStax Enterprise support
- βVector search (5.0) & CDC
- β15-min response SLA
- βDedicated Cassandra architect
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Why Choose SubscribeIT for Cassandra?
Cassandra Specialists Engineers
Our team holds DataStax certifications with extensive experience managing planet-scale Cassandra deployments handling billions of operations daily.
Proactive Repair Management
Automated repair orchestration using Cassandra Reaper ensures data consistency across massive distributed clusters without manual intervention.
Security & Compliance
Comprehensive security with client-to-node and node-to-node encryption, role-based access control, and audit logging meeting SOC 2 requirements.
Performance Optimization
Expert tuning of compaction strategies, read/write paths, and caching layers. We analyze partition distribution and optimize query patterns for sub-millisecond latency.
Query-Driven Data Modeling
We design optimal schemas based on your access patterns, leveraging partition keys, clustering columns, and materialized views for maximum performance.
Multi-Cloud Expertise
Deploy on AWS, GCP, Azure, or bare metal. We architect multi-DC topologies for geographic distribution and disaster recovery.
Technology Stack & Integrations
We Work With Your Entire Cassandra Ecosystem
Frequently Asked Questions
What Cassandra versions do you support?βΌ
We support Apache Cassandra 3.x through the latest 5.0 release. Our primary focus is on Cassandra 4.0/4.1 (stable) and 5.0 (latest with vector search). We also work with DataStax Enterprise editions.
How do you handle repairs in large clusters?βΌ
We use Cassandra Reaper for automated repair orchestration. Reaper schedules incremental repairs across the cluster with configurable intensity to avoid performance impact. For 1000+ node clusters, we implement segmented repair strategies with careful coordination across data centers.
Whatβs your approach to data modeling?βΌ
We follow query-driven data modeling principles. First, we analyze your access patterns and queries. Then we design partition keys for even distribution, clustering columns for sort order, and leverage denormalization where appropriate. We use materialized views sparingly and prefer multiple tables optimized for specific queries.
Can you deploy Cassandra on Kubernetes?βΌ
Yes. We specialize in cloud-native Cassandra deployments using the K8ssandra operator. This provides automated scaling, backup management with Medusa, repair scheduling with Reaper, and monitoring with Prometheus/Grafana - all integrated into your Kubernetes environment.
How do you achieve sub-millisecond latency?βΌ
Performance tuning involves multiple layers: optimal compaction strategy selection (STCS for writes, LCS for reads, TWCS for time-series), read/write path optimization, proper caching configuration (key cache, row cache), SSTable distribution analysis, and LOCAL consistency levels to avoid cross-DC latency. We also tune JVM heap and GC settings.
What backup and disaster recovery options do you provide?βΌ
For backups, we use Medusa which provides automated snapshot management with S3/GCS storage and efficient incremental backups. For disaster recovery, we architect multi-DC replication using NetworkTopologyStrategy with appropriate consistency levels. In enterprise deployments, we maintain active-active configurations across geographic regions for zero-downtime failover.