Big Data Service

Oracle Big Data Service is a fully managed, automated cloud service that provides enterprises with a cost-effective Hadoop environment. Customers easily create secure and scalable Hadoop-based data lakes that can quickly process large amounts of data.

Oracle Big Data Service features

Flexible Hadoop cluster provisioning

Oracle Big Data Service makes it easy for customers to deploy Hadoop clusters of all sizes, with VM shapes ranging from 1 OCPU to dedicated bare metal environments. Customers choose between high-performance NVMe storage or cost-effective block storage, and can grow or shrink their clusters.

Simplified data security and availability

Oracle Big Data Service simplifies the process of making Hadoop clusters both highly available and secure. Based on Oracle best practices, Big Data Service implements high availability and security with a single click, reducing the need for in-depth Hadoop skills.

Oracle Cloud SQL

Oracle Cloud SQL, an available add-on service, enables customers to initiate Oracle SQL queries on data in HDFS, Kafka, and Oracle Cloud Infrastructure Object Storage. Any user, application, or analytics tool can work transparently with these data stores, using push-down, scale-out processing to minimize data movement and speed queries.

Oracle Machine Learning for SparkR

Oracle Machine Learning for SparkR gives data scientists the functions to manipulate data stored in Apache Hadoop Distributed File System (HDFS), Spark DataFrames, and other Java Database Connectivity (JDBC) sources. They can also build machine learning models in R for easy deployment with Apache Spark using high-performance libraries with scalable, parallelized algorithms. Oracle Machine Learning for SparkR lets users take advantage of all Oracle Big Data Service cluster nodes, and is easily accessed either through the included notebook or a customer-installed notebook.

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Complete, integrated big data solution

Oracle Big Data Service is easy for customers to use and manage because it interoperates with data integration, data science, and analytics services, while enabling developers to easily access data using Oracle SQL. Enterprises can eliminate data silos and ensure that data lakes are not isolated from other corporate data sources.

Oracle Big Data Service use cases

Build a cloud data lake with Oracle Big Data Service

Quickly create Hadoop-based data lakes to extend or complement customer data warehouses and ensure that all data is both easily accessible and managed cost-effectively.

Read the blog
Develop machine learning (ML) models

Query, visualize, and transform data so data scientists can build ML models using the included notebook with its R, Python, and SQL support.

Read the blog
Migrate on-premises Hadoop clusters to the cloud

Move customer-managed Hadoop clusters to a fully managed, cloud-based service, reducing management costs and improving resource utilization.

Read the data management technical brief (PDF)

Big Data Service pricing

Cost Estimator

Oracle Big Data Service

Product	Comparison Price ( /vCPU)*	Unit Price	Unit
OCI - Compute - Standard			OCPU per hour
OCI - Compute - Dense I/O			OCPU per hour
OCI - Compute - HPC			OCPU per hour
Oracle Cloud SQL			OCPU per hour
Oracle Big Data Service – service fee			OCPU per hour

*To make it easier to compare pricing across cloud service providers, Oracle web pages show both vCPU (virtual CPUs) prices and OCPU (Oracle CPU) prices for products with compute-based pricing. The products themselves, provisioning in the portal, billing, etc. continue to use OCPU (Oracle CPU) units. OCPUs represent physical CPU cores. Most CPU architectures, including x86, execute two threads per physical core, so 1 OCPU is the equivalent of 2 vCPUs for x86-based compute. The per-hour OCPU rate customers are billed at is therefore twice the vCPU price since they receive two vCPUs of compute power for each OCPU, unless it’s a sub-core instance such as preemptible instances. Additional details supporting the difference between OCPU vs. vCPU can be accessed here.