
Big Data & Analytics
Apache Iceberg
Our Apache Iceberg Services help organizations manage large-scale analytical data with high-performance, reliability, and flexibility. As an open-source software support provider, we specialize in deploying, configuring, optimizing, and managing Apache Iceberg to enable efficient data lake management, time travel, schema evolution, and seamless integration with modern analytics engines.
Key Service Propositions
Next-Gen Table Format for Data Lakes
Achieve ACID-compliant, scalable, and high-performance big data processing.
Multi-Engine Compatibility
Seamlessly integrate Iceberg with Apache Spark, Trino, Presto, Flink, Dremio, and Hive.
Optimized Storage & Query Performance
Reduce query latency and storage costs with metadata pruning and partitioning.
Schema Evolution & Time Travel
Enable real-time schema changes and historical data access without disruptions.
Hybrid & Multi-Cloud Support
Deploy Iceberg on AWS, Azure, GCP, Kubernetes, and on-premises environments.
Security & Governance
Implement data encryption, access control, and compliance frameworks for enterprise-grade security.
Service Offerings
Apache Iceberg Deployment & Configuration
Data Lake Table Format Implementation –
Deploy Apache Iceberg as a scalable, ACID-compliant table format.
Multi-Cloud & Hybrid Deployments –
Configure Iceberg for AWS S3, Azure ADLS, Google Cloud Storage, HDFS, and MinIO.
Metadata Management & Optimization –
Tune metadata pruning, partitioning, and compaction strategies.
Custom Table Format Strategies –
Design Iceberg tables to handle structured, semi-structured, and unstructured data.
Performance Optimization & Query Acceleration
Partitioning & Predicate Pushdown –
Optimize query performance with hidden partitioning and metadata pruning.
Compaction & File Format Optimization –
Implement Parquet, ORC, or Avro for efficient storage and query execution.
Vectorized Query Execution –
Enable faster analytical processing with columnar data structures.
Benchmarking & Performance Tuning –
Analyze and optimize query execution across Spark, Flink, and Trino.
Schema Evolution & Data Versioning
Schema Evolution Without Downtime –
Modify table structures without breaking queries or data pipelines.
Time Travel & Snapshot Isolation –
Access historical data at any point in time for reproducibility and auditing.
Rollback & Version Control –
Restore previous table states without complex migrations or downtime.
Multi-Table Transactions –
Ensure ACID compliance for concurrent writes and updates.
Security, Governance & Access Control
Role-Based Access Control (RBAC) –
Implement fine-grained permissions for data access.
Data Encryption & Compliance –
Secure Iceberg data with TLS encryption, masking, and GDPR/HIPAA compliance.
Audit Logging & Data Lineage –
Track table modifications and data usage for compliance reporting.
Data Governance Integration –
Connect Iceberg with Apache Ranger, AWS Lake Formation, and other governance tools.
Apache Iceberg Integration & Data Processing
Apache Spark, Flink & Trino Integration –
Optimize Iceberg for fast, scalable analytical queries.
ETL & Data Ingestion Pipelines –
Design efficient batch and streaming ingestion workflows.
Data Lakehouse Architecture –
Unify structured and unstructured data processing in a single platform.
Streaming & Change Data Capture (CDC) –
Enable real-time data ingestion with Kafka, Debezium, and Flink.
Managed Apache Iceberg Services & Support
24/7 Monitoring & SLA-Backed Support –
Ensure high availability with proactive monitoring and incident resolution.
Automated Upgrades & Patch Management –
Keep Apache Iceberg secure and up-to-date.
Disaster Recovery & Backup Strategies –
Implement snapshot replication, multi-region backups, and failover solutions.
Training & Knowledge Transfer –
Hands-on Apache Iceberg training for data engineering and analytics teams.
Supported Workloads
Cloud Data Lakes & Lakehouses
Real-Time & Batch Analytics
Machine Learning & AI Pipelines
Financial Services & Risk Analysis
E-Commerce & Personalization
IoT & Event Streaming

