Cloudera Named a Visionary in the Gartner MQ for Cloud DBMS

Cloudera Named a Visionary in the Gartner MQ for Cloud DBMS

We’re excited to share that Gartner has recognized Cloudera as a Visionary among all vendors evaluated in the 2023 Gartner® Magic Quadrant™ for Cloud Database Management Systems. This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. 

Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics. Our customers run some of the world’s most innovative, largest, and most demanding data science, data engineering, analytics, and AI use cases, including PB-size generative AI workloads. Cloudera has over 25 Exabytes of high-value business data under management, making us one of the larger data hyperscalers in this MQ. This recognition is a testament to our vision and ability as a strategic partner to deliver an open and interoperable Cloud data platform, with the flexibility to use the best fit data services and low code, no code Generative AI infused practitioner tools.

Download the complimentary 2023 Gartner Magic Quadrant for Cloud Database Management Systems report

The Gartner Magic Quadrant report is complemented with the Gartner Critical Capabilities for Analytics report which scores all the vendors on their technical strengths. We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies. Our cutting-edge Shared data experience (SDX) service provides a unified control plane for common security, governance and metadata management on all structured and unstructured data. This is critical for our customers to gain visibility into all their data, residing anywhere, and deliver trusted, secure data for all analytics and AI workloads. Moreover, the portability and interoperability of our data services bring simplicity, flexibility, and agility to all data workloads. 

Download the complimentary 2023 Gartner Critical Capabilities for Analytics Report to view the technical scores of each vendor on the three key analytic use cases. 

The following are key attributes of our platform that set Cloudera apart:

Unlock the Value of Data While Accelerating Analytics and AI

The data lakehouse revolutionizes the ability to unlock the power of data. It unifies structured data with unstructured data giving a holistic view of the business and enhancing the efficacy of AI by providing it with more structured and accessible business data as context. By bringing data warehouse-like capabilities to the lake it eliminates the need for multiple data stores, simplifies data engineering pipelines, increases data reliability, and improves the efficiency of both data scientists and data analysts. Cloudera’s open data lakehouse accelerates BI query performance by over 40% while also making it easy for data scientists to explore the latest datasets for their models. The integrated data services from stream analytics, data flow, and data engineering to data warehousing and machine learning all operate on a single copy of data residing in Iceberg tables for a true multi-function analytics experience. 

This improves collaboration across teams, empowers users with self-service data access and reduces compute and storage requirements while minimizing integration tax. It gives the flexibility to teams to use their choice of tools/engines without worrying about ETL. Cloudera’s real-time streaming service is unique in the industry because it not only delivers microbatch ingestion like other intelligent data platforms but also provides stream ingestion and stream data processing so you can process the stream in real time before ingesting the events into the lakehouse.

Guarantee Data Ecosystem Interoperability

Many organizations struggle to unlock the full value of data due to disparate tools and data sources, and poor data quality. Organizations manage an increasing variety of single purpose databases, resulting in increased cost, complexity, management overhead, and risk.

Cloudera customers deploy a very diverse data infrastructure that consists of hundreds of data sources, multiple clouds, and multiple processing engines. Our commitment to open source, investments in integrating open standards, and building open APIs ensures that our platform and services interoperate in any data ecosystem. With the integration of Apache Iceberg table format, we allow any compute engine to access data from Cloudera’s data lakehouse including engines outside of our platform like Snowflake, Google Big Query, AWS Redshift, and more. This has helped our customers reduce their Snowflake and Databricks cloud costs while still using the tool of their choice. 

Democratize Data, Analytics, and AI 

As per a study conducted by Harvard Business School, The Wharton School, The Warwick Business School, and MIT Sloan, Generative AI can improve a highly skilled worker’s performance by as much as 40% compared with workers who don’t use it.

At Cloudera, we are embedding AI in all our products to improve productivity of data professionals. These intelligent services automate tasks, optimize workloads, simplify UI, and make it easier for more users to interact with the data. \

We have embedded LLMs in our Hue interface so you can write SQL queries in English or any other language. LLMs in our data visualization tool allow business users to talk to their data using a chatbot and share dashboards and reports with ease. LLMs in our Cloudera Machine Learning (CML) service intelligently assist you in data science and AI projects. AI in our Observability solution optimizes your workloads and makes recommendations based on your specific usage. All this intelligence built into the platform democratizes data, analytics, and AI. 

We are also continuously building tools and services to help organizations build AI applications with Cloudera. Cloudera’s quick starter AI projects called AMPs package the code, models, datasets, and configurations required to deploy a new ML project, accelerating the speed of deploying new LLM use cases by 50%. Unlike software, ML models need continuous tuning. They need to be monitored and refreshed continuously to prevent model drift. Cloudera’s MLFlow service monitors models and makes it easy to unplug and plug new models as and when needed. Cloudera’s real-time streaming service ensures you are fine-tuning your models with the latest data to prevent model drift and accelerate the rate of learning. The private cloud data services and write once read anywhere portability guarantee that you can use LLMs without ever leaking your company secrets to the public while reducing the inference costs.

Deliver Trusted Data for Trusted AI

Trusted AI needs trusted data. This is data that is reliable, complete, fully understood and has the right business context. Data that has lineage so you can trace back the source and all the processing it underwent. Increased confidence in data results in trusted AI. Cloudera’s data catalog combined with the Shared Data Experience (SDX) service gives full visibility into the data so you can find your datasets easily, understand your data with lineage and metadata information, and access the right data with unified security and governance. 

Adopt Data Mesh to Power the New Wave of AI

Data is evolving from a valuable asset to being treated as a product. Adopting the data mesh philosophy is not merely a trend but a strategic imperative to unlock the true power of data. This approach is vital to gaining a deeper understanding of data, using it to drive actionable insights, and building a repository of trusted data that is maintainable, portable, and easily shareable across diverse teams. The essence of data mesh lies in transferring the ownership of data into the hands of the users and creators and amplifying the utility of data across various use cases.

Implementing a data mesh requires changing the organization’s data culture and elevating data literacy across all teams. The tools and platform play a pivotal role in increasing the visibility of data, easing its manageability, facilitating data product sharing, and delivering federated governance across all data assets. Cloudera’s lakehouse with integrated portable data services, SDX, and data catalog capabilities along with data flow service for integrating data from literally any source, has helped companies implement a data mesh fostering global collaboration and information sharing across teams.

Empower Customers to Take Back Control of Their Data:

Only Cloudera lets you take back control of your data, workloads, deployment, and spend. With the Cloudera data lakehouse, you have full control of your data, with the flexibility to store it in the format you like, run your workloads on whichever cloud you want, and process it with whatever engine you like. All this without any vendor lock-ins or additional ingress or egress costs and while having full control over your cloud spend. Cloudera’s industry-leading financial governance capabilities and observability solution help you minimize cloud spend and storage costs giving you full visibility into your workloads. We also see customers reducing their cloud spend by repatriating non-fluctuating workloads to private cloud where they get all the benefits of cloud for instance—scale, flexibility, and agility—while maintaining full control over their cloud spend

Generative AI has accelerated the adoption of AI. But before you jump into Generative AI and LLMs, companies need strong data fundamentals. Data sitting in swamps is of no use until it can be made actionable with the right analytics and AI. LLM’s ability to mine unstructured data is remarkable which has unleashed new business use cases and enhanced the ability to respond to customer requests, present personalized offers, and accelerate R&D. Cloudera customers like OCBC have already deployed LLMs using their enterprise data as context to improve customer experience and operational efficiency. 

Cloudera’s hybrid, multi-cloud data platform delivers the strong data fundamentals you need to accelerate your Generative AI journey. Sign up for a trial to see for yourself

Navita Sood
Director Product Marketing, Modern Data Architectures
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