Contact Us
Is your company considering a data-driven approach? You are in the right place. Contact us to set up a centralized data repository — a data lake — on any cloud provider: AWS (S3), GCP (Cloud Storage), or Azure (Blob Storage). We seamlessly connect your data lake to the respective data catalog (AWS Glue, GCP Dataplex, Unity Catalog), enabling AI/ML, Business Intelligence, and analytics teams to discover and leverage your data for informed decision-making.
We accelerate your Data Lake and data warehouse implementation with pre-built, highly configurable, and cloud-agnostic ETL/ELT pipelines — a Do It Yourself (DIY) approach. We ingest data from multiple sources into your preferred cloud storage as a data lake, using your choice of open table format:
- Apache Iceberg — our primary format for GCP Lakehouse products
- Apache Hudi
- Delta Lake
- ACID-like transaction guarantees
- Record-level upserts and deletes
- Schema evolution and time travel
- Optimized read/write performance (CoW vs MoR)
- BigQuery
- Redshift
- Azure Synapse Analytics
- Snowflake
We also provide Terraform code for infrastructure provisioning and integrate ETL/ELT pipelines with your orchestration tool of choice (Airflow, Dagster, Prefect, etc.). Our specializations include:
- Terraform code for cloud resource provisioning (compute, storage, catalog)
- ETL/ELT pipeline implementation codebase
- Integration of provisioned resources with ETL/ELT pipelines
- Role-based and row/column-level access control for data catalog
Our Ready-to-Deploy Products
We offer the following production-ready pipeline codebases — each deployable into your own cloud account:
- RDBMS to Data Lake — batch, incremental, and CDC pipelines from MySQL, PostgreSQL, SQL Server, Oracle, AWS Aurora, and GCP Cloud SQL into Apache Iceberg, Hudi, or Delta Lake.
- GCP Cloud SQL → Iceberg Lakehouse — HOCON-driven Spark JDBC-to-Iceberg ELT pipeline on GCP Dataproc Serverless with incremental checkpoints, upserts, and Airflow/Livy orchestration. Up to 98% cheaper than Google Cloud Datastream.
- GCS Files → Iceberg Lakehouse — checkpoint-driven Spark pipeline for Parquet, CSV, JSON, and Avro files on GCS into Apache Iceberg with idempotency guards and full schema inference. Significantly cheaper than GCP Managed Iceberg Tables.
- Semi-Structured Sources to Data Lake — MongoDB, DynamoDB, Firestore, Cassandra, and JSON/XML feeds on AWS, GCP, or Azure.
- Unstructured Data to Data Lake — CSV, Parquet, Avro, ORC, and web API response ingestion pipelines.
- Data Lake to Data Warehouse — sync curated lake tables into BigQuery, Redshift, Snowflake, or Azure Synapse Analytics via YAML/HOCON configuration.
Why Choose Us for Your Data Lake or Lakehouse?
We specialize in open table format storage and metadata-driven data cataloguing — enabling your Analytics, AI/ML, and Business Intelligence teams to query data through AWS Athena, Presto, Trino, or BigQuery SQL interfaces.
- Certified Architects: AWS Certified Data Engineer and GCP Professional Data Engineer on your team.
- Fast Time to Production: From PoC to production in 8–12 weeks for structured, semi-structured, or unstructured source pipelines (Apache Hudi / Iceberg / Delta Lake / XTable).
- Proven Cost Savings: Our GCP Iceberg pipelines are up to 98% cheaper than managed GCP ingestion services — see our Datastream and BigLake Managed Iceberg cost benchmarks.
- Cost Guarantee: 30% lower pipeline cost vs. in-house team development.
- Custom Solutions: We tailor every pipeline to your specific source, destination, and orchestration requirements.
- Dedicated Support: Our engineers are available at every step — from architecture review to production deployment.
By Contacting Us, You Can Expect:
- A free consultation with our data engineers to discuss your specific needs and source/destination requirements.
- Expert guidance on choosing the right pipeline product — RDBMS, GCS files, NoSQL, or Data Lake to Warehouse.
- Insights into best practices for data management, governance, and cost optimization.
- A roadmap for leveraging your data for AI/ML and business intelligence.
- A proposal, implementation plan, and delivery timeline tailored to your organization.
