AI-Driven Streaming Lakehouse Platform
Realfuture
One platform for data in motion and the systems it reaches.
Realfuture brings catalogs, AI-assisted development and diagnosis, Flink and Flink CDC, and lakehouse systems into one operating workflow. Build and validate pipelines with shared metadata, publish them to supported runtimes, and connect Paimon lake tables, Fluss streaming storage, and Doris or StarRocks analytics.
01 / Catalog & metadata
Reuse the data definitions your team works with.
Browse databases, streams and lakehouse tables through built-in and external catalogs. Manage supported objects with forms or SQL, and reuse metadata in authoring, validation and exploration.
- Discover tables and inspect columns, types and DDL.
- Filter Kafka topics and infer schemas from supported message formats.
- Manage tables, views and functions within a workspace.
02 / AI-assisted development
Develop with AI and the context of your data.
Use AI to draft SQL, CDC configuration and ETL definitions with schema context. Combine suggestions with SQL completion, validation and previews, or develop from existing JARs and Git builds.
- Generate and refine SQL or CDC configuration; review changes before applying them.
- Configure ETL field mappings, filters and joins; inspect the generated SQL.
- Query supported databases through Native SQL to inspect source or target data.
03 / Flink & Flink CDC
Process streams and keep databases in sync.
Build Flink SQL and Flink CDC pipelines for continuous processing and data movement. Configure whole-database synchronization, table routing, row filters, field mappings, transformations and supported schema evolution.
- Develop continuous transformations, joins and aggregations with Flink SQL.
- Create CDC pipelines from connector templates or AI-assisted drafts.
- Validate source, target and schema-change behavior for the selected connector versions.
04 / Lakehouse & analytics
Connect storage, processing and real-time analytics.
Use Paimon for lake tables, Fluss for streaming storage, and Doris or StarRocks for analytics. Realfuture connects these systems through catalogs, supported connectors, query workflows and component-specific maintenance.
- Explore Paimon and Fluss tables alongside Doris, StarRocks and database catalogs.
- Write through supported SQL or CDC connectors and inspect target data through the appropriate query path.
- Run adapted Paimon Actions for compaction, snapshots and branch or tag maintenance.
05 / Production operations
Investigate jobs with their runtime context.
Keep resources, releases and runtime evidence with the workload. Publish to supported runtimes, then inspect status, metrics, logs, checkpoints and history through the same workspace.
- Organize connectors, formats, UDFs and application resources, with draft and Git-based publishing workflows.
- Operate supported standalone, YARN and Kubernetes environments and manage checkpoint-based recovery.
- Ask AI to diagnose a job using scoped, read-only metrics, logs, checkpoints and exceptions.
Enterprise engineering
Enterprise engineering across the data stack.
Realfuture develops and maintains enhancements across the platform, catalogs, Flink, Flink CDC and ecosystem integrations. Enterprise services cover deployment, migration, troubleshooting and maintenance for the agreed components.
Catalogs, connectors and query engines have distinct support scopes. AI uses configured model providers; generated changes are reviewed before use. Component versions, model access and services are agreed for the selected release.