Top Vendors for Apache Hudi, Apache Iceberg, Delta Lake Data Lakehouse Ingestion
The data lake revolution continues, but getting data in — ingestion — remains a critical hurdle. Most vendors are just doing the minimum to support the open table format (just write the file). This article explores the top vendors who are simplifying data lake ingestion while supporting modern table formats like Apache Iceberg, Apache Hudi, and Delta Lake with advanced table optimization services (clustering, cleaning, file resizing, and compaction services that provide 10x query performance over “just writing the file” query performance).
The Rise of Modern Table Formats
Data lakes hold immense potential, but unstructured data poses challenges for querying and analysis. Modern table formats like Iceberg, Hudi, and Delta Lake address this by bringing structure and ACID (Atomicity, Consistency, Isolation, Durability) guarantees to data lakes. These formats offer benefits such as:
- Schema Evolution: Adapt to changing data structures without rewriting entire datasets.
- Time Travel: Access historical versions of data for auditing or rollbacks.
- Upserts and Deletes: Efficiently update and remove data, ensuring data quality.
Top Vendors for Modern Data Lake Ingestion
Several vendors are leading the charge in simplifying data lake ingestion while supporting modern table formats. Let’s explore four key players:
1. Fivetran: A leader in cloud-based data integration, Fivetran offers pre-built connectors to extract data from over 150 sources. It seamlessly integrates with data lakes like Amazon S3, Snowflake, and Databricks, supporting Apache Iceberg as the destination format. Fivetran offer only Iceberg compaction table optimization services.
2. Upsolver: This platform takes a code-free approach to data lake ingestion. Users visually configure pipelines that extract, transform, and load (ETL) data into various data lakes. Upsolver supports Apache Iceberg as a destination format. They also offer only Iceberg compaction table optimization services.
3. Onehouse.ai: This unique solution combines data ingestion with a data lakehouse platform and offers row-level data updates on the lake. It offers pre-built connectors for various data sources and supports all three major data lakehouse table formats — Apache Hudi, Apache Iceberg and Delta Lake. Additionally, Onehouse.ai provides built-in data governance and security features, ideal for organizations with strict data compliance requirements. Onehouse offers compaction, file resizing, cleaning and clustering table optimization services.
Choosing the Right Vendor
The best vendor depends on your specific needs. Here are some factors to consider:
- Data Sources: Does the vendor offer connectors for the data sources you need?
- Technical Expertise: Do you require a code-free solution or prefer more flexibility with custom code?
- Modern Table Formats: Does the vendor support your preferred table format (Iceberg, Hudi or Delta Lake or all of them)? What table optimization services to they provide (major features are clustering, compaction, file resizing, and cleaning)?
- Costs: Is the solution cost efficient?
- Scalability: Can the solution handle your current and anticipated data volume?
- Security and Compliance: Does the vendor meet your data governance and security requirements?
Conclusion
By embracing modern table formats and leveraging dedicated data lake ingestion tools, businesses can unlock the full potential of their data lakes. Fivetran, Upsolver, Onehouse.ai, and other vendors offer innovative solutions that simplify data ingestion while ensuring data quality and structure. By carefully evaluating your needs and comparing vendor offerings, you can select the best solution to build a robust and efficient data lake foundation.
