Enterprise-grade Big Data platforms on Hadoop, deployable on AWS EMR, Microsoft Azure, or your own private cloud infrastructure.
When your data outgrows traditional databases, you need an architecture built for scale from the ground up. We implement Hadoop-based Big Data platforms that process petabytes reliably — whether on-premise or on managed cloud services. Our engineers have designed and tuned clusters handling billions of events per day, and we bring that experience to every engagement.
Right-sizing, hardware selection, HDFS configuration, YARN resource management, and high-availability setup for production workloads.
Batch and incremental data loading workflows using Sqoop, Oozie, and Spark — from ingestion through transformation to analytical layers.
Event-driven architectures with Kafka and Flink for sub-second latency. We design systems that process millions of events per second.
Structured analytics layers (Hive, Impala, Presto) on top of raw data lakes — enabling self-service SQL analytics at Big Data scale.
Fully managed cloud Hadoop implementations that reduce operational overhead while keeping costs predictable. Cloud-native from day one.
Job optimization, memory tuning, data skew resolution, and cluster monitoring dashboards. We make slow jobs fast.
Processing data at scale? Let's talk architecture.
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