We build with Apache Cassandra
We use Apache Cassandra to build fault-tolerant, horizontally scalable data stores for high-volume applications that support your business goals. From data modeling and cluster architecture to replication and performance tuning, we create products designed to evolve with your needs.
DISCUSS YOUR PROJECTMasterless Architecture
No master node means no single point of failure.
Linear Horizontal Scale
Add nodes to grow capacity across regions without downtime.
Tunable Consistency
Choose consistency and latency tradeoffs on a per-query basis.
BENEFITS OF APACHE CASSANDRA technology
We use Apache Cassandra to handle write-heavy workloads, keep clusters available across regions, and scale capacity linearly.
BUILD
[01]- Model query patterns
- Design partition keys
- Configure replication
- Set consistency levels
ENGAGE
[02]- Handle write-heavy loads
- Serve low-latency reads
- Stream data via Kafka
- Support multi-region access
GROW
[03]- Scale nodes linearly
- Add new data centers
- Tune compaction strategy
- Extend with Spark analytics
Our Apache Cassandra Technology Stack
We combine Apache Cassandra with Apache Kafka, Apache Spark, and DataStax tooling for streaming ingestion, analytics, and cluster operations. The stack is selected around your access patterns and availability requirements.
Custom Apache Cassandra development company
With our Apache Cassandra development services, we build highly available data layers for write-heavy applications, IoT telemetry platforms, messaging systems, and time-series workloads, tailored to your boldest business goals. Having years of experience with Cassandra, our engineers harness its masterless architecture and tunable consistency to deliver resilient, always-on infrastructure across industries and company sizes. Whether it's migrating from a relational database or standing up a new multi-region cluster from scratch, we model data around your real query patterns so performance holds as traffic grows. Our range of Apache Cassandra development services spans consulting, data modeling, cluster deployment, and ongoing operations. We work as your technical partner and ensure complete transparency and comfortable communication throughout the process, bringing deep distributed systems expertise and a pragmatic approach to schema design and problem-solving. All this to make sure your cluster stays available and fast as usage grows, and moves your business forward.
OUR APACHE CASSANDRA SERVICES
We build, modernize, and support Apache Cassandra clusters around your product goals.
ACCELERATE FEATURE DEVELOPMENT
Your roadmap is growing faster than your team. Add senior engineering capacity and deliver more without sacrificing quality.
Cassandra Data Modeling
Query-first schema design and migrations from relational or other NoSQL databases, built around your access patterns.
Cassandra Multi-Region Clusters
Masterless, multi-datacenter deployments with tunable consistency for applications that need to stay available worldwide.
Cassandra Streaming & Analytics
Real-time pipelines connected to Kafka and Spark for ingestion, analytics, and event-driven workloads.
Cassandra Modernization
Migrate legacy databases to Cassandra or optimize an existing cluster's partitioning and compaction strategy.
Meet our Apache Cassandra experts
A curated selection of senior specialists currently available for new engagements.
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Frequently Asked Questions
Common questions about how we use Apache Cassandra and what it can bring to your project. Have a specific requirement?
How does SoftDoes use Apache Cassandra?
We use Apache Cassandra to build highly available data layers for write-heavy applications, IoT telemetry, messaging platforms, and time-series workloads. We design partition keys and consistency levels around your product's access patterns and availability requirements.
What types of applications do you build with Cassandra?
We build IoT telemetry platforms, messaging systems, recommendation engines, and time-series applications that need to handle heavy write throughput without downtime.
Can Cassandra integrate with our existing data infrastructure?
Yes. Applications connect through the DataStax drivers for Java, Python, Node.js, Go, and C#, Kafka Connect moves events in and out of Cassandra tables, and the Spark Cassandra Connector lets analytics jobs read and write data directly.
Do you migrate data from relational databases to Cassandra?
Yes. Moving to Cassandra means redesigning tables around queries, since there are no joins: usually one denormalized table per read path. We often dual-write during cutover, bulk load history with Spark or DSBulk, and compare row counts before switching reads.
When should we use Cassandra instead of a relational database?
Choose Cassandra when write volume, multi-datacenter replication, or always-on availability outgrow a single primary database and your query patterns are known up front. Keep PostgreSQL or MySQL when you need joins, multi-row transactions, or flexible ad hoc reporting.
Can you help optimize an existing Cassandra cluster?
Yes. In Cassandra clusters we usually find wide or hot partitions, tombstone buildup from deletes and TTLs, and mismatched compaction strategies. Fixes range from TimeWindowCompactionStrategy for time-series tables to remodeling partition keys and scheduling regular repairs.
How do you decide whether Cassandra fits a project?
Cassandra fits when every query the product needs can be answered from a known partition key and the workload is write-heavy or multi-region. If access patterns are still changing, we start relational; without in-house operators, Amazon Keyspaces or DataStax Astra reduce operational load.
