Best Data Integration Tools for Java

Diffusion is the pioneer of real-time data streaming solutions and messaging. The company was founded to solve real-time system & application connectivity challenges and data distribution problems faced by companies around the world. It has an international team consisting of business and tech experts. The Diffusion dataplatform, the company's flagship product, makes it simple to consume, enrich and deliver data. Quickly capitalize on new or existing data sources. Diffusion is designed to simplify real-time, event-driven application development. It allows you to quickly add new capabilities at minimal development costs. Accepts any size, format or velocity of data. The flexible, hierarchical model organizes event-data incoming in a topic tree structure with multiple levels. Scalable to millions of topics. Low-code features in the platform facilitate transformation of event data. Enables subscription to event-data at a fine-grained level for hyper-personalization.

All your data needs can be met by a powerful platform. From data ingestion/integration, transformation, and storage to knowledge catalog, graph networks, data analytics, governance, monitoring, and, sharing. An AI/ML Platform that allows enterprises to train, test and troubleshoot models, deploy them, and govern them at scale. This will boost productivity, while maintaining model performance with confidence in production. AutoML is a dedicated solution that allows you to train models with minimum effort or CustomML allows you to train your own case-specific models. You can now connect ML logic with data. Integrating your protocols and authorization models with an integrated exploration of possible action. Extreme configurability is at your disposal. Use internal lineage system for alerting and impact analyses. Interwoven with security paradigm; provides unalterable tracking

The smart semantic layer unifies metrics and speeds up the delivery of data products by 90% with shorter SQL queries. Model data using business terms for a common meaning and to align business metrics. Define semantic relationships to replace JOINs, making queries much easier. Hierarchies and classifications can help you better understand data. Automatically map data into the semantic model. Join multiple data sources using a powerful SQL engine distributed to query data at a large scale. Consume data in the form of a semantically connected graph. Materialized views and an intelligent cache engine can boost performance and reduce compute costs. Advanced query optimizations are available. Connect to any file format, cloud, datalake, data warehouse, or database. Timbr allows you to work seamlessly with your data sources. Timbr optimizes a query and pushes it to the backend when a query is executed.