Enhancing Real-Time Data Integration for AI Applications
In the rapidly evolving landscape of artificial intelligence, the demand for real-time data is paramount. However, the integration of data from legacy systems often presents significant challenges. Traditional ETL (Extract, Transform, Load) pipelines can introduce latency and complexity, leading to outdated intelligence that hampers the performance of applications powered by large language models (LLMs) and Retrieval-Augmented Generation (RAG). For enterprises leveraging the Postgres stack, establishing a seamless connection between operational data and real-time AI capabilities is essential.
Open-source Postgres has emerged as a favored back-end database for developers aiming to meet operational demands. Building upon this robust foundation, Neon introduces an innovative approach to database creation through AI agents. Recently, Databricks unveiled Lakebase, a fully managed Postgres database that has gained traction as a preferred platform for developing AI applications, following its acquisition of Neon.
In this context, Striim is thrilled to announce an expansion of its Postgres offerings, facilitating high-throughput ingestion from Neon into Databricks for real-time analytics. Additionally, Striim enables rapid data delivery from legacy systems into Neon, promoting platform and data modernization. The unified Striim platform empowers developers to construct vector embeddings directly within the data pipeline, ensuring that real-time data flows seamlessly into both Neon and Databricks for the development of agentic AI use cases.
With Striim, developers can effortlessly migrate, integrate, or replicate transactional and event data, alongside in-flight vector embeddings and enriched, high-quality data from various operational stores into Neon. This modern integration framework allows for the swift construction of advanced agentic applications, with Neon serving as the transactional backbone.
This enhanced capability offers organizations a range of benefits:
- Effortlessly replicate operational data in real-time from traditional systems such as Oracle, PostgreSQL, MySQL, and SQL Server, ensuring zero downtime and automated schema evolution.
- Facilitate real-time ingestion and Change Data Capture (CDC) from Neon into Databricks, guaranteeing that AI models and analytics workloads are consistently fed with fresh data.
- Support Retrieval-Augmented Generation (RAG) and generative AI applications natively within Neon or Databricks, complete with inline data enrichment and vector embeddings.
- Stream event data from Apache Kafka into Neon in real time, removing the reliance on fragile batch-based integrations.
- Uphold comprehensive data governance with in-flight AI-driven PII detection and resolution, encryption, and support for customer-managed keys.
“By extending our platform to support Neon and Databricks, we’re equipping Postgres-native teams with the necessary tools to construct real-time, AI-native architectures without the need to overhaul their existing stack,” remarked Alok Pareek, co-founder and Executive Vice President of Engineering and Products at Striim. “Our mission is to assist customers in transitioning from legacy platforms and outdated ETL processes to real-time, agent-driven intelligence. Striim’s Vector Agent, along with Neon’s CDC and delivery capabilities, brings us closer to realizing that vision.”
This expansion builds upon Striim’s growing partnership with Databricks, which includes support for Databricks Delta Lake using open Delta table formats, as well as the introduction of SQL2Fabric-X, unlocking real-time SQL Server data for both Microsoft Fabric and Azure Databricks. With Neon now integrated into the Striim ecosystem, Postgres users can embrace this modernization wave, streaming operational data to empower AI and analytics without compromising on performance or reliability.
For further information regarding Striim’s support for Neon and Databricks, please visit www.striim.com/connectors/databricks/ or reach out to our team at sales@striim.com.
