Technology/ Open Source/ Apache Iceberg

Apache Iceberg

Table foundations for an open data lake architecture

We provide Apache Iceberg consulting, implementation, migration, table optimization, and technical support. We help organizations organize analytical data using an open table format, with clear integration between storage, catalogs, and processing engines.

Table foundations for an open data lake architecture

Our services focus on the systems that create, query, and maintain Iceberg tables. We work with your data engineering and platform teams to review table design, write patterns, metadata, and maintenance so that the data lake remains understandable as it grows.

We provide Apache Iceberg consulting, implementation, migration, table optimization, and technical support. We help organizations organize analytical data using an open table format, with clear integration between storage, catalogs, and processing engines.

Our services focus on the systems that create, query, and maintain Iceberg tables. We work with your data engineering and platform teams to review table design, write patterns, metadata, and maintenance so that the data lake remains understandable as it grows.

What we do

Our Apache Iceberg Services

01 / 10

Architecture and Compatibility Assessment

Design the relationship between Iceberg tables, their catalog, object storage, and query engines. We review the required read and write operations against component compatibility so that architectural decisions reflect the workloads your team actually needs to run.

  • Catalog and engine assessment
  • Storage integration planning
  • Read and write compatibility review
  • Platform dependency mapping

02 / 10

Catalog and Storage Integration

Configure the selected catalog and storage connections used to manage Iceberg tables. We validate permissions, connectivity, and table registration, then document the dependencies that operators need to preserve during platform changes and incident recovery.

  • Catalog configuration
  • Storage access and credentials
  • Table registration and discovery
  • Integration validation and documentation

03 / 10

Table Design and Partition Strategy

Organize tables around their data and access patterns. We review schemas, partition transforms, sort order, and file characteristics, and test representative workloads to find a maintainable balance between write behavior and analytical query performance.

  • Schema and table design
  • Partition strategy assessment
  • Sort order and file layout
  • Data type compatibility checks

04 / 10

Ingestion and Processing Workflows

Help data engineering teams write and update Iceberg tables through the selected engines. We review ingestion patterns, concurrent operations, and application requirements, then validate that the chosen combinations produce the expected data and table state.

  • Spark processing integration
  • Batch and streaming write review
  • Merge and update workflow validation
  • Concurrent write testing

05 / 10

Migration and Data Validation

Plan the move from existing file layouts or table formats to Iceberg. We assess conversion options, reconcile source and target results, and prepare a cutover approach that considers the applications and jobs depending on the data.

  • Source table assessment
  • Conversion and loading procedures
  • Record and query reconciliation
  • Cutover and rollback planning

06 / 10

Table Maintenance and Performance

Keep table and metadata growth under review as data accumulates. We plan compaction and other maintenance using the capabilities of the selected engine, with attention to workload impact, retention requirements, and query performance.

  • Small-file and metadata assessment
  • File compaction planning
  • Manifest maintenance review
  • Query and write performance testing

07 / 10

Snapshot Retention and Recovery Planning

Define how snapshots and data files should be retained and cleaned up. We review dependencies before maintenance, test available rollback procedures, and distinguish table snapshots from the wider backup arrangements needed for catalogs and storage.

  • Snapshot retention policies
  • Snapshot rollback validation
  • Orphan file cleanup safeguards
  • Catalog and storage recovery planning

08 / 10

Monitoring, Upgrades, and Operational Support

Make table health and maintenance activity visible to the people running the platform. We review failed writes, metadata growth, and component changes, and validate compatibility when catalogs, engines, libraries, or table features are updated.

  • Write and maintenance monitoring
  • Table health checks
  • Engine and format compatibility assessment
  • Upgrade validation and runbooks

09 / 10

Technical Support

Get help with failed commits, catalog connectivity problems, small-file growth, slow table access, schema changes, and retention-related incidents. We examine the available evidence, coordinate investigation across the relevant components, and help your team identify corrective actions.

Support arrangements define the covered environment, service hours, communication channels, priorities, and escalation process. This gives your team a clear route for requesting assistance and following an issue through investigation, validation, and closure.

  • Incident investigation and troubleshooting
  • Configuration and integration assistance
  • Root-cause analysis within the agreed scope
  • Resolution guidance and incident documentation

10 / 10

Training and Knowledge Transfer

Build practical understanding of table design, catalog dependencies, engine compatibility, compaction, snapshot retention, and recovery procedures. We tailor sessions to the environment and the responsibilities of the people developing, administering, and supporting it.

Workshops can use your configuration, representative examples, and agreed operating scenarios. Documentation and runbook walkthroughs help your team apply the knowledge after the engagement.

  • Role-focused technical workshops
  • Configuration and workflow walkthroughs
  • Troubleshooting and maintenance guidance
  • Documentation and operational handover

A practical approach to Apache Iceberg

We evaluate table changes across every engine that must read or write the data. Maintenance procedures include retention checks and ownership, helping your team avoid removing files that are still required by an active workload or recovery plan.

We agree the work and acceptance checks with your team, validate changes in a suitable environment, and document the outcome. Clear handover makes the configuration, operating procedures, and next actions easier to maintain after delivery.

Supported Versions and Support Hours

Supported versions

Versions below were confirmed against upstream release information on 15 October 2026. We reconfirm them at the start of each engagement.

  • Apache Iceberg 1.12, tested with Spark, Flink and Trino.

Support hours

Standard support is delivered in business hours, Monday to Saturday, India Standard Time. Coverage hours, response targets and escalation steps for each severity are defined in the service agreement. Upstream response times are outside our control.

Get in touch

Discuss Your Apache Iceberg Requirements

Building an Iceberg data lake or improving the maintenance of existing tables? Tell us about your catalogs, storage, processing engines, and data workloads so we can plan the work.

Apache Iceberg, Iceberg, Apache and the Apache feather logo are registered trademarks or trademarks of the Apache Software Foundation in the United States and other countries. Their use here implies no endorsement by the Apache Software Foundation. We are an independent service provider and are not affiliated with, endorsed by or sponsored by the Apache Software Foundation or the project.