Query-First Data Modeling
We design partition keys, clustering columns, and denormalized tables around each query your application runs, keeping partitions bounded and avoiding the tombstone buildup that slows reads.
Database Technologies
Cassandra Support & Consulting
Keep Cassandra Fast as Data and Traffic Grow
Apache Cassandra rewards good design and punishes shortcuts. Our consultants design data models, build and tune clusters, and support Cassandra in production for teams running write-heavy, always-on workloads on premises or in managed cloud services.
What We Deliver
Where We Make the Difference
Most Cassandra problems trace back to a data model built like a relational schema, or to compaction and repair left on defaults. We model tables around your queries, set consistency levels deliberately, and tune the cluster against real traffic before it goes live.
Tunable Consistency by Design
We set replication factors with NetworkTopologyStrategy and choose consistency levels such as LOCAL_QUORUM per operation, balancing latency against correctness across your data centers.
Compaction and Repair Tuning
We match compaction strategy to each table, TimeWindow for time series and Leveled for read-heavy data, and schedule repairs with Cassandra Reaper so replicas stay consistent.
Managed Cassandra Options
Amazon Keyspaces, Azure Managed Instance for Apache Cassandra, and DataStax Astra DB remove cluster operations. We assess their compatibility and cost against running Cassandra yourself.
Our Approach
How We Deliver Cassandra Support & Consulting
Step 1: Map Every Query
We list the reads and writes your application performs, estimate partition sizes and growth, and design tables that answer each query from a single partition.
Step 2: Design the Topology
We plan nodes, racks, data centers, and replication, choose hardware or instance types, and set JVM and compaction settings suited to your workload.
Step 3: Load Test Before Launch
We drive production-like traffic with cassandra-stress or NoSQLBench, watch latency percentiles and compaction backlog, and adjust until results meet your targets.
Step 4: Run It Day to Day
We set up monitoring, repair schedules, backups, and runbooks for node replacement and scaling, then support the cluster or train your team to run it.
Is Cassandra the right database for our workload?
Cassandra fits write-heavy, high-availability workloads with predictable query patterns, such as time series, event logs, and user activity. It is a poor fit for ad hoc queries and joins, and we will tell you if another database suits you better.
Our Cassandra reads keep getting slower. Can you help?
Yes. Slow reads usually come from oversized partitions, tombstones, or compaction falling behind. We find the cause in cluster metrics and fix the data model or settings behind it.
Should we move to a managed Cassandra service?
Managed services cut operational work but differ in feature support, pricing, and tuning control. We compare them against your current cluster before you commit.
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