SAN FRANCISCO, CA — May 14, 2025 — Databricks, the Data and AI company, today announced its intent to acquire Neon, a leading serverless Postgres company. As the $100-billion-plus database market braces for unprecedented disruption driven by AI, Databricks plans to continue innovating and investing in Neon’s database and developer experience for existing and new Neon customers and partners.| Databricks
SAN FRANCISCO, CA — August 19, 2025 — Databricks, the Data and AI company, today announced it has signed a term sheet for its Series K round, which it expects to close soon with backing from existing investors. This funding values the company at >$100 billion.| Databricks
LakehouseIQ by Databricks uses generative AI to provide contextual answers to natural language questions, enhancing data accessibility and governance.| Databricks
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Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.| Databricks
Databricks has announced a partnership and participation in the Series A funding of Mistral AI, one of Europe's leading providers of generative AI solutions. Databricks and Mistral AI now offer Mistral AI’s open models natively integrated within the Databricks Data Intelligence Platform.| Databricks
Apache Hadoop ecosystem refers to the various components of the Hadoop software library; it includes open source projects and a complete range of tools.| Databricks
We are excited to announce the release of the Databricks AI Security Framework (DASF) version 1.0 whitepaper! Machine learning (ML) and generative AI (GenAI) are transforming the future of work by enhancing innovation, competitiveness, and employee productivity. However, organizations are grappling with the dual challenge of leveraging artificial intelligence (AI) technologies for opportunities while managing potential security and privacy risks, such as data breaches and regulatory complianc...| Databricks
The Big Book of Generative AI: Best practices for building production-quality GenAI applications. Learn to build, deploy, and fine-tune models with code samples and expert insights.| Databricks
To build customer support bots, internal knowledge graphs, or Q&A systems, customers often use Retrieval Augmented Generation (RAG) applications which leverage pre-trained models together with their proprietary data. However, the lack of guardrails for secure credential management and abuse prevention prohibits customers from democratizing access and development of these applications. We recently announced the MLflow AI Gateway, a highly scalable, enterprise-grade API gateway that enables org...| Databricks
Enhance RAG and generative AI applications with Databricks Vector Search, offering fast, secure similarity search over unstructured documents.| Databricks
Enhance RAG applications with real-time structured data using Databricks' Feature and Function Serving, simplifying Gen AI application deployment.| Databricks
Speed up GenAI app development with Databricks' new foundation model capabilities, offering best practices for production-quality applications.| Databricks
This blog post discusses best practices for evaluating retrieval-augmented generation (RAG) applications using large language models (LLMs).| Databricks
Databricks unveils Lakehouse AI, enhancing generative AI development with new tools for LLMs, vector search, and comprehensive AI lifecycle management.| Databricks
Understand the transition from traditional data architectures to the modern data lakehouse, combining the best of data lakes and data warehouses.| Databricks
Learn how ACID transactions have long been one of the most enviable properties of data warehouses, but Delta Lake has now brought them to data lakes.| Databricks
Today, we are excited to introduce DBRX, an open, general-purpose LLM created by Databricks. Across a range of standard benchmarks, DBRX sets a new state-of-the-art for established open LLMs. Moreover, it provides the open community and enterprises building their own LLMs with capabilities that were previously limited to closed model APIs; according to our measurements, it surpasses GPT-3.5, and it is competitive with Gemini 1.0 Pro. It is an especially capable code model, surpassing speciali...| Databricks
Learn how Databricks combines rules-based and machine learning models to combat financial fraud with collaborative tools and SQL functionalities.| Databricks
The combined companies plan to make generative AI accessible to any size organization, enabling them to build, own and secure generative AI models with their data.| Databricks
Retrieval augmented generation or RAG is an architectural approach that pulls your data as context for large language models (LLMs) to improve relevancy.| Databricks
Databricks SQL enables high-performance analytics with SQL on large datasets. Simplify data analysis and unlock insights with an intuitive, scalable platform.| Databricks
Training large language models (LLMs) costs less than you think. Using the MosaicML platform, we show how fast, cheap, and easy it is to train these models at scale (1B -> 70B parameters). With new training recipes and infrastructure designed for large workloads, we enable you to train LLMs while maintaining total customizability over your model and dataset.| Databricks
Learn more about the open source file format Apache Parquet, its applications in data science, and its advantages over CSV and TSV formats.| Databricks
With a Data Intelligence Engine that understands your data’s uniqueness, the Databricks Platform allows you to infuse AI into every facet of your business.| Databricks
Photon is the next generation engine on the Databricks Lakehouse Platform that provides extremely fast query performance at low cost. Learn more here.| Databricks
We benchmarked LLM training on a multi-node AMD MI250 cluster and found near-linear scaling on up to 128 GPUs, demonstrating a compelling option for multi-node LLM training.| Databricks
A medallion architecture is a data design pattern used to logically organize data in a lakehouse, with the goal of improving the structure and quality of data.| Databricks
Understand MLOps, the practice of deploying and maintaining machine learning models in production reliably and efficiently, with Databricks.| Databricks
Today, we’re excited to share that we’ve completed our acquisition of MosaicML, a leading platform for creating and customizing generative AI models for your enterprise. Since the founding of Databricks, our mission has been to democratize data and AI for every enterprise. Generative AI will power the next wave of enterprise data applications, and together with MosaicML, we plan to provide the best-in-class experience for training, customizing, and deploying generative AI applications.| Databricks
Learn how orchestration is the coordination and management of multiple computer systems, applications and/or services, stringing together multiple tasks.| Databricks
Learn more about the new data management paradigm data lakehouses -- its evolution, adoption, common use cases, and its advantages over previous systems and technologies.| Databricks
